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This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id</primary_keys>"
<foreign_keys>[Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the ids of the students who either registered or attended a course?</question>
[SQL]:
| <SQL_QUERY>SELECT student_id FROM student_course_registrations UNION SELECT student_id FROM student_course_attendance</SQL_QUERY> | student_assessment | SELECT student_id FROM student_course_registrations UNION SELECT student_id FROM student_course_attendance | What are the ids of the students who either registered or attended a course? | [Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text); | [Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id | [Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id</primary_keys>"
<foreign_keys>[Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the id of courses which are registered or attended by student whose id is 121?</question>
[SQL]:
| <SQL_QUERY>SELECT course_id FROM student_course_registrations WHERE student_id = 121 UNION SELECT course_id FROM student_course_attendance WHERE student_id = 121</SQL_QUERY> | student_assessment | SELECT course_id FROM student_course_registrations WHERE student_id = 121 UNION SELECT course_id FROM student_course_attendance WHERE student_id = 121 | Find the id of courses which are registered or attended by student whose id is 121? | [Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text); | [Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id | [Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id</primary_keys>"
<foreign_keys>[Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the ids of the courses that are registered or attended by the student whose id is 121?</question>
[SQL]:
| <SQL_QUERY>SELECT course_id FROM student_course_registrations WHERE student_id = 121 UNION SELECT course_id FROM student_course_attendance WHERE student_id = 121</SQL_QUERY> | student_assessment | SELECT course_id FROM student_course_registrations WHERE student_id = 121 UNION SELECT course_id FROM student_course_attendance WHERE student_id = 121 | What are the ids of the courses that are registered or attended by the student whose id is 121? | [Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text); | [Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id | [Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id</primary_keys>"
<foreign_keys>[Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are all info of students who registered courses but not attended courses?</question>
[SQL]:
| <SQL_QUERY>SELECT * FROM student_course_registrations WHERE student_id NOT IN (SELECT student_id FROM student_course_attendance)</SQL_QUERY> | student_assessment | SELECT * FROM student_course_registrations WHERE student_id NOT IN (SELECT student_id FROM student_course_attendance) | What are all info of students who registered courses but not attended courses? | [Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text); | [Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id | [Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id</primary_keys>"
<foreign_keys>[Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are all details of the students who registered but did not attend any course?</question>
[SQL]:
| <SQL_QUERY>SELECT * FROM student_course_registrations WHERE student_id NOT IN (SELECT student_id FROM student_course_attendance)</SQL_QUERY> | student_assessment | SELECT * FROM student_course_registrations WHERE student_id NOT IN (SELECT student_id FROM student_course_attendance) | What are all details of the students who registered but did not attend any course? | [Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text); | [Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id | [Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id</primary_keys>"
<foreign_keys>[Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the id of students who registered course statistics in the order of registration date.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.student_id FROM courses AS T1 JOIN student_course_registrations AS T2 ON T1.course_id = T2.course_id WHERE T1.course_name = "statistics" ORDER BY T2.registration_date</SQL_QUERY> | student_assessment | SELECT T2.student_id FROM courses AS T1 JOIN student_course_registrations AS T2 ON T1.course_id = T2.course_id WHERE T1.course_name = "statistics" ORDER BY T2.registration_date | List the id of students who registered course statistics in the order of registration date. | [Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text); | [Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id | [Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id</primary_keys>"
<foreign_keys>[Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the ids of the students who registered course statistics by order of registration date?</question>
[SQL]:
| <SQL_QUERY>SELECT T2.student_id FROM courses AS T1 JOIN student_course_registrations AS T2 ON T1.course_id = T2.course_id WHERE T1.course_name = "statistics" ORDER BY T2.registration_date</SQL_QUERY> | student_assessment | SELECT T2.student_id FROM courses AS T1 JOIN student_course_registrations AS T2 ON T1.course_id = T2.course_id WHERE T1.course_name = "statistics" ORDER BY T2.registration_date | What are the ids of the students who registered course statistics by order of registration date? | [Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text); | [Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id | [Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id</primary_keys>"
<foreign_keys>[Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the id of students who attended statistics courses in the order of attendance date.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.student_id FROM courses AS T1 JOIN student_course_attendance AS T2 ON T1.course_id = T2.course_id WHERE T1.course_name = "statistics" ORDER BY T2.date_of_attendance</SQL_QUERY> | student_assessment | SELECT T2.student_id FROM courses AS T1 JOIN student_course_attendance AS T2 ON T1.course_id = T2.course_id WHERE T1.course_name = "statistics" ORDER BY T2.date_of_attendance | List the id of students who attended statistics courses in the order of attendance date. | [Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text); | [Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id | [Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text);</schema>"
<primary_keys>[Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id</primary_keys>"
<foreign_keys>[Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the ids of the students who attended courses in the statistics department in order of attendance date.</question>
[SQL]:
| <SQL_QUERY>SELECT T2.student_id FROM courses AS T1 JOIN student_course_attendance AS T2 ON T1.course_id = T2.course_id WHERE T1.course_name = "statistics" ORDER BY T2.date_of_attendance</SQL_QUERY> | student_assessment | SELECT T2.student_id FROM courses AS T1 JOIN student_course_attendance AS T2 ON T1.course_id = T2.course_id WHERE T1.course_name = "statistics" ORDER BY T2.date_of_attendance | What are the ids of the students who attended courses in the statistics department in order of attendance date. | [Schema (values) (types)]: | student_assessment | Addresses : address_id (text) , line_1 (number) , line_2 (text) , city (text) , zip_postcode (text) , state_province_county (text) , country (text) | People : person_id (text) , first_name (number) , middle_name (text) , last_name (text) , cell_mobile_number (text) , email_address (text) , login_name (text) , password (text) | Students : student_id (text) , student_details (number) | Courses : course_id (text) , course_name (number) , course_description (text) , other_details (text) | People_Addresses : person_address_id (text) , person_id (number) , address_id (text) , date_from (text) , date_to (text) | Student_Course_Registrations : student_id (text) , course_id (number) , registration_date (text) | Student_Course_Attendance : student_id (text) , course_id (number) , date_of_attendance (text) | Candidates : candidate_id (text) , candidate_details (number) | Candidate_Assessments : candidate_id (text) , qualification (number) , assessment_date (text) , asessment_outcome_code (text); | [Primary Keys]: addresses : address_id, people : person_id, students : student_id, courses : course_id, people_addresses : person_address_id, student_course_registrations : student_id, student_course_attendance : student_id, candidates : candidate_id, candidate_assessments : candidate_id | [Foreign Keys]: students : student_id = people : person_id | people_addresses : address_id = addresses : address_id | people_addresses : person_id = people : person_id | student_course_registrations : course_id = courses : course_id | student_course_registrations : student_id = students : student_id | student_course_attendance : student_id = student_course_registrations : student_id | student_course_attendance : course_id = student_course_registrations : course_id | candidates : candidate_id = people : person_id | candidate_assessments : candidate_id = candidates : candidate_id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Give me the dates when the max temperature was higher than 85.</question>
[SQL]:
| <SQL_QUERY>SELECT date FROM weather WHERE max_temperature_f > 85</SQL_QUERY> | bike_1 | SELECT date FROM weather WHERE max_temperature_f > 85 | Give me the dates when the max temperature was higher than 85. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the dates with a maximum temperature higher than 85?</question>
[SQL]:
| <SQL_QUERY>SELECT date FROM weather WHERE max_temperature_f > 85</SQL_QUERY> | bike_1 | SELECT date FROM weather WHERE max_temperature_f > 85 | What are the dates with a maximum temperature higher than 85? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of stations that have latitude lower than 37.5?</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM station WHERE lat < 37.5</SQL_QUERY> | bike_1 | SELECT name FROM station WHERE lat < 37.5 | What are the names of stations that have latitude lower than 37.5? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of all stations with a latitude smaller than 37.5?</question>
[SQL]:
| <SQL_QUERY>SELECT name FROM station WHERE lat < 37.5</SQL_QUERY> | bike_1 | SELECT name FROM station WHERE lat < 37.5 | What are the names of all stations with a latitude smaller than 37.5? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each city, return the highest latitude among its stations.</question>
[SQL]:
| <SQL_QUERY>SELECT city , max(lat) FROM station GROUP BY city</SQL_QUERY> | bike_1 | SELECT city , max(lat) FROM station GROUP BY city | For each city, return the highest latitude among its stations. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each city, what is the highest latitude for its stations?</question>
[SQL]:
| <SQL_QUERY>SELECT city , max(lat) FROM station GROUP BY city</SQL_QUERY> | bike_1 | SELECT city , max(lat) FROM station GROUP BY city | For each city, what is the highest latitude for its stations? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Give me the start station and end station for the trips with the three oldest id.</question>
[SQL]:
| <SQL_QUERY>SELECT start_station_name , end_station_name FROM trip ORDER BY id LIMIT 3</SQL_QUERY> | bike_1 | SELECT start_station_name , end_station_name FROM trip ORDER BY id LIMIT 3 | Give me the start station and end station for the trips with the three oldest id. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the station station and end station for the trips with the three smallest ids?</question>
[SQL]:
| <SQL_QUERY>SELECT start_station_name , end_station_name FROM trip ORDER BY id LIMIT 3</SQL_QUERY> | bike_1 | SELECT start_station_name , end_station_name FROM trip ORDER BY id LIMIT 3 | What is the station station and end station for the trips with the three smallest ids? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average latitude and longitude of stations located in San Jose city?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(lat) , avg(long) FROM station WHERE city = "San Jose"</SQL_QUERY> | bike_1 | SELECT avg(lat) , avg(long) FROM station WHERE city = "San Jose" | What is the average latitude and longitude of stations located in San Jose city? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average latitude and longitude in San Jose?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(lat) , avg(long) FROM station WHERE city = "San Jose"</SQL_QUERY> | bike_1 | SELECT avg(lat) , avg(long) FROM station WHERE city = "San Jose" | What is the average latitude and longitude in San Jose? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the id of the trip that has the shortest duration?</question>
[SQL]:
| <SQL_QUERY>SELECT id FROM trip ORDER BY duration LIMIT 1</SQL_QUERY> | bike_1 | SELECT id FROM trip ORDER BY duration LIMIT 1 | What is the id of the trip that has the shortest duration? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the id of the shortest trip?</question>
[SQL]:
| <SQL_QUERY>SELECT id FROM trip ORDER BY duration LIMIT 1</SQL_QUERY> | bike_1 | SELECT id FROM trip ORDER BY duration LIMIT 1 | What is the id of the shortest trip? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the total and maximum duration of trips with bike id 636?</question>
[SQL]:
| <SQL_QUERY>SELECT sum(duration) , max(duration) FROM trip WHERE bike_id = 636</SQL_QUERY> | bike_1 | SELECT sum(duration) , max(duration) FROM trip WHERE bike_id = 636 | What is the total and maximum duration of trips with bike id 636? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the total and maximum duration for all trips with the bike id 636?</question>
[SQL]:
| <SQL_QUERY>SELECT sum(duration) , max(duration) FROM trip WHERE bike_id = 636</SQL_QUERY> | bike_1 | SELECT sum(duration) , max(duration) FROM trip WHERE bike_id = 636 | What is the total and maximum duration for all trips with the bike id 636? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each zip code, return the average mean temperature of August there.</question>
[SQL]:
| <SQL_QUERY>SELECT zip_code , avg(mean_temperature_f) FROM weather WHERE date LIKE "8/%" GROUP BY zip_code</SQL_QUERY> | bike_1 | SELECT zip_code , avg(mean_temperature_f) FROM weather WHERE date LIKE "8/%" GROUP BY zip_code | For each zip code, return the average mean temperature of August there. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each zip code, what is the average mean temperature for all dates that start with '8'?</question>
[SQL]:
| <SQL_QUERY>SELECT zip_code , avg(mean_temperature_f) FROM weather WHERE date LIKE "8/%" GROUP BY zip_code</SQL_QUERY> | bike_1 | SELECT zip_code , avg(mean_temperature_f) FROM weather WHERE date LIKE "8/%" GROUP BY zip_code | For each zip code, what is the average mean temperature for all dates that start with '8'? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>From the trip record, find the number of unique bikes.</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT bike_id) FROM trip</SQL_QUERY> | bike_1 | SELECT count(DISTINCT bike_id) FROM trip | From the trip record, find the number of unique bikes. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many different bike ids are there?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT bike_id) FROM trip</SQL_QUERY> | bike_1 | SELECT count(DISTINCT bike_id) FROM trip | How many different bike ids are there? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the number of distinct cities the stations are located at?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT city) FROM station</SQL_QUERY> | bike_1 | SELECT count(DISTINCT city) FROM station | What is the number of distinct cities the stations are located at? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many different cities have these stations?</question>
[SQL]:
| <SQL_QUERY>SELECT count(DISTINCT city) FROM station</SQL_QUERY> | bike_1 | SELECT count(DISTINCT city) FROM station | How many different cities have these stations? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many stations does Mountain View city has?</question>
[SQL]:
| <SQL_QUERY>SELECT COUNT(*) FROM station WHERE city = "Mountain View"</SQL_QUERY> | bike_1 | SELECT COUNT(*) FROM station WHERE city = "Mountain View" | How many stations does Mountain View city has? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many stations are in Mountain View?</question>
[SQL]:
| <SQL_QUERY>SELECT COUNT(*) FROM station WHERE city = "Mountain View"</SQL_QUERY> | bike_1 | SELECT COUNT(*) FROM station WHERE city = "Mountain View" | How many stations are in Mountain View? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Return the unique name for stations that have ever had 7 bikes available.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.name FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id WHERE T2.bikes_available = 7</SQL_QUERY> | bike_1 | SELECT DISTINCT T1.name FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id WHERE T2.bikes_available = 7 | Return the unique name for stations that have ever had 7 bikes available. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the different names for each station that has ever had 7 bikes available?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT T1.name FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id WHERE T2.bikes_available = 7</SQL_QUERY> | bike_1 | SELECT DISTINCT T1.name FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id WHERE T2.bikes_available = 7 | What are the different names for each station that has ever had 7 bikes available? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which start station had the most trips starting from August? Give me the name and id of the station.</question>
[SQL]:
| <SQL_QUERY>SELECT start_station_name , start_station_id FROM trip WHERE start_date LIKE "8/%" GROUP BY start_station_name ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | bike_1 | SELECT start_station_name , start_station_id FROM trip WHERE start_date LIKE "8/%" GROUP BY start_station_name ORDER BY COUNT(*) DESC LIMIT 1 | Which start station had the most trips starting from August? Give me the name and id of the station. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the start station's name and id for the one that had the most start trips in August?</question>
[SQL]:
| <SQL_QUERY>SELECT start_station_name , start_station_id FROM trip WHERE start_date LIKE "8/%" GROUP BY start_station_name ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | bike_1 | SELECT start_station_name , start_station_id FROM trip WHERE start_date LIKE "8/%" GROUP BY start_station_name ORDER BY COUNT(*) DESC LIMIT 1 | What are the start station's name and id for the one that had the most start trips in August? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which bike traveled the most often in zip code 94002?</question>
[SQL]:
| <SQL_QUERY>SELECT bike_id FROM trip WHERE zip_code = 94002 GROUP BY bike_id ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | bike_1 | SELECT bike_id FROM trip WHERE zip_code = 94002 GROUP BY bike_id ORDER BY COUNT(*) DESC LIMIT 1 | Which bike traveled the most often in zip code 94002? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the id of the bike that traveled the most in 94002?</question>
[SQL]:
| <SQL_QUERY>SELECT bike_id FROM trip WHERE zip_code = 94002 GROUP BY bike_id ORDER BY COUNT(*) DESC LIMIT 1</SQL_QUERY> | bike_1 | SELECT bike_id FROM trip WHERE zip_code = 94002 GROUP BY bike_id ORDER BY COUNT(*) DESC LIMIT 1 | What is the id of the bike that traveled the most in 94002? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many days had both mean humidity above 50 and mean visibility above 8?</question>
[SQL]:
| <SQL_QUERY>SELECT COUNT(*) FROM weather WHERE mean_humidity > 50 AND mean_visibility_miles > 8</SQL_QUERY> | bike_1 | SELECT COUNT(*) FROM weather WHERE mean_humidity > 50 AND mean_visibility_miles > 8 | How many days had both mean humidity above 50 and mean visibility above 8? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the number of days that had an average humity above 50 and an average visibility above 8?</question>
[SQL]:
| <SQL_QUERY>SELECT COUNT(*) FROM weather WHERE mean_humidity > 50 AND mean_visibility_miles > 8</SQL_QUERY> | bike_1 | SELECT COUNT(*) FROM weather WHERE mean_humidity > 50 AND mean_visibility_miles > 8 | What is the number of days that had an average humity above 50 and an average visibility above 8? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the latitude, longitude, city of the station from which the shortest trip started?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.lat , T1.long , T1.city FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.start_station_id ORDER BY T2.duration LIMIT 1</SQL_QUERY> | bike_1 | SELECT T1.lat , T1.long , T1.city FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.start_station_id ORDER BY T2.duration LIMIT 1 | What is the latitude, longitude, city of the station from which the shortest trip started? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the latitude, longitude, and city of the station from which the trip with smallest duration started?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.lat , T1.long , T1.city FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.start_station_id ORDER BY T2.duration LIMIT 1</SQL_QUERY> | bike_1 | SELECT T1.lat , T1.long , T1.city FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.start_station_id ORDER BY T2.duration LIMIT 1 | What is the latitude, longitude, and city of the station from which the trip with smallest duration started? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the ids of stations that are located in San Francisco and have average bike availability above 10.</question>
[SQL]:
| <SQL_QUERY>SELECT id FROM station WHERE city = "San Francisco" INTERSECT SELECT station_id FROM status GROUP BY station_id HAVING avg(bikes_available) > 10</SQL_QUERY> | bike_1 | SELECT id FROM station WHERE city = "San Francisco" INTERSECT SELECT station_id FROM status GROUP BY station_id HAVING avg(bikes_available) > 10 | What are the ids of stations that are located in San Francisco and have average bike availability above 10. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the ids of the stations in San Francisco that normally have more than 10 bikes available?</question>
[SQL]:
| <SQL_QUERY>SELECT id FROM station WHERE city = "San Francisco" INTERSECT SELECT station_id FROM status GROUP BY station_id HAVING avg(bikes_available) > 10</SQL_QUERY> | bike_1 | SELECT id FROM station WHERE city = "San Francisco" INTERSECT SELECT station_id FROM status GROUP BY station_id HAVING avg(bikes_available) > 10 | What are the ids of the stations in San Francisco that normally have more than 10 bikes available? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names and ids of stations that had more than 14 bikes available on average or were installed in December?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , T1.id FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id GROUP BY T2.station_id HAVING avg(T2.bikes_available) > 14 UNION SELECT name , id FROM station WHERE installation_date LIKE "12/%"</SQL_QUERY> | bike_1 | SELECT T1.name , T1.id FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id GROUP BY T2.station_id HAVING avg(T2.bikes_available) > 14 UNION SELECT name , id FROM station WHERE installation_date LIKE "12/%" | What are the names and ids of stations that had more than 14 bikes available on average or were installed in December? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names and ids of all stations that have more than 14 bikes available on average or had bikes installed in December?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , T1.id FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id GROUP BY T2.station_id HAVING avg(T2.bikes_available) > 14 UNION SELECT name , id FROM station WHERE installation_date LIKE "12/%"</SQL_QUERY> | bike_1 | SELECT T1.name , T1.id FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id GROUP BY T2.station_id HAVING avg(T2.bikes_available) > 14 UNION SELECT name , id FROM station WHERE installation_date LIKE "12/%" | What are the names and ids of all stations that have more than 14 bikes available on average or had bikes installed in December? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the 3 most common cloud cover rates in the region of zip code 94107?</question>
[SQL]:
| <SQL_QUERY>SELECT cloud_cover FROM weather WHERE zip_code = 94107 GROUP BY cloud_cover ORDER BY COUNT (*) DESC LIMIT 3</SQL_QUERY> | bike_1 | SELECT cloud_cover FROM weather WHERE zip_code = 94107 GROUP BY cloud_cover ORDER BY COUNT (*) DESC LIMIT 3 | What is the 3 most common cloud cover rates in the region of zip code 94107? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the 3 most common cloud covers in the zip code of 94107?</question>
[SQL]:
| <SQL_QUERY>SELECT cloud_cover FROM weather WHERE zip_code = 94107 GROUP BY cloud_cover ORDER BY COUNT (*) DESC LIMIT 3</SQL_QUERY> | bike_1 | SELECT cloud_cover FROM weather WHERE zip_code = 94107 GROUP BY cloud_cover ORDER BY COUNT (*) DESC LIMIT 3 | What are the 3 most common cloud covers in the zip code of 94107? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the zip code in which the average mean sea level pressure is the lowest?</question>
[SQL]:
| <SQL_QUERY>SELECT zip_code FROM weather GROUP BY zip_code ORDER BY avg(mean_sea_level_pressure_inches) LIMIT 1</SQL_QUERY> | bike_1 | SELECT zip_code FROM weather GROUP BY zip_code ORDER BY avg(mean_sea_level_pressure_inches) LIMIT 1 | What is the zip code in which the average mean sea level pressure is the lowest? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the zip code that has the lowest average mean sea level pressure?</question>
[SQL]:
| <SQL_QUERY>SELECT zip_code FROM weather GROUP BY zip_code ORDER BY avg(mean_sea_level_pressure_inches) LIMIT 1</SQL_QUERY> | bike_1 | SELECT zip_code FROM weather GROUP BY zip_code ORDER BY avg(mean_sea_level_pressure_inches) LIMIT 1 | What is the zip code that has the lowest average mean sea level pressure? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average bike availability in stations that are not located in Palo Alto?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(bikes_available) FROM status WHERE station_id NOT IN (SELECT id FROM station WHERE city = "Palo Alto")</SQL_QUERY> | bike_1 | SELECT avg(bikes_available) FROM status WHERE station_id NOT IN (SELECT id FROM station WHERE city = "Palo Alto") | What is the average bike availability in stations that are not located in Palo Alto? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average bike availablility for stations not in Palo Alto?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(bikes_available) FROM status WHERE station_id NOT IN (SELECT id FROM station WHERE city = "Palo Alto")</SQL_QUERY> | bike_1 | SELECT avg(bikes_available) FROM status WHERE station_id NOT IN (SELECT id FROM station WHERE city = "Palo Alto") | What is the average bike availablility for stations not in Palo Alto? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the average longitude of stations that never had bike availability more than 10?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(long) FROM station WHERE id NOT IN (SELECT station_id FROM status GROUP BY station_id HAVING max(bikes_available) > 10)</SQL_QUERY> | bike_1 | SELECT avg(long) FROM station WHERE id NOT IN (SELECT station_id FROM status GROUP BY station_id HAVING max(bikes_available) > 10) | What is the average longitude of stations that never had bike availability more than 10? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the mean longitude for all stations that have never had more than 10 bikes available?</question>
[SQL]:
| <SQL_QUERY>SELECT avg(long) FROM station WHERE id NOT IN (SELECT station_id FROM status GROUP BY station_id HAVING max(bikes_available) > 10)</SQL_QUERY> | bike_1 | SELECT avg(long) FROM station WHERE id NOT IN (SELECT station_id FROM status GROUP BY station_id HAVING max(bikes_available) > 10) | What is the mean longitude for all stations that have never had more than 10 bikes available? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>When and in what zip code did max temperature reach 80?</question>
[SQL]:
| <SQL_QUERY>SELECT date , zip_code FROM weather WHERE max_temperature_f >= 80</SQL_QUERY> | bike_1 | SELECT date , zip_code FROM weather WHERE max_temperature_f >= 80 | When and in what zip code did max temperature reach 80? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What zip codes have a station with a max temperature greater than or equal to 80 and when did it reach that temperature?</question>
[SQL]:
| <SQL_QUERY>SELECT date , zip_code FROM weather WHERE max_temperature_f >= 80</SQL_QUERY> | bike_1 | SELECT date , zip_code FROM weather WHERE max_temperature_f >= 80 | What zip codes have a station with a max temperature greater than or equal to 80 and when did it reach that temperature? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Give me ids for all the trip that took place in a zip code area with average mean temperature above 60.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.id FROM trip AS T1 JOIN weather AS T2 ON T1.zip_code = T2.zip_code GROUP BY T2.zip_code HAVING avg(T2.mean_temperature_f) > 60</SQL_QUERY> | bike_1 | SELECT T1.id FROM trip AS T1 JOIN weather AS T2 ON T1.zip_code = T2.zip_code GROUP BY T2.zip_code HAVING avg(T2.mean_temperature_f) > 60 | Give me ids for all the trip that took place in a zip code area with average mean temperature above 60. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each zip code, find the ids of all trips that have a higher average mean temperature above 60?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.id FROM trip AS T1 JOIN weather AS T2 ON T1.zip_code = T2.zip_code GROUP BY T2.zip_code HAVING avg(T2.mean_temperature_f) > 60</SQL_QUERY> | bike_1 | SELECT T1.id FROM trip AS T1 JOIN weather AS T2 ON T1.zip_code = T2.zip_code GROUP BY T2.zip_code HAVING avg(T2.mean_temperature_f) > 60 | For each zip code, find the ids of all trips that have a higher average mean temperature above 60? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each zip code, return how many times max wind speed reached 25?</question>
[SQL]:
| <SQL_QUERY>SELECT zip_code , count(*) FROM weather WHERE max_wind_Speed_mph >= 25 GROUP BY zip_code</SQL_QUERY> | bike_1 | SELECT zip_code , count(*) FROM weather WHERE max_wind_Speed_mph >= 25 GROUP BY zip_code | For each zip code, return how many times max wind speed reached 25? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each zip code, how many times has the maximum wind speed reached 25 mph?</question>
[SQL]:
| <SQL_QUERY>SELECT zip_code , count(*) FROM weather WHERE max_wind_Speed_mph >= 25 GROUP BY zip_code</SQL_QUERY> | bike_1 | SELECT zip_code , count(*) FROM weather WHERE max_wind_Speed_mph >= 25 GROUP BY zip_code | For each zip code, how many times has the maximum wind speed reached 25 mph? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>On which day and in which zip code was the min dew point lower than any day in zip code 94107?</question>
[SQL]:
| <SQL_QUERY>SELECT date , zip_code FROM weather WHERE min_dew_point_f < (SELECT min(min_dew_point_f) FROM weather WHERE zip_code = 94107)</SQL_QUERY> | bike_1 | SELECT date , zip_code FROM weather WHERE min_dew_point_f < (SELECT min(min_dew_point_f) FROM weather WHERE zip_code = 94107) | On which day and in which zip code was the min dew point lower than any day in zip code 94107? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which days had a minimum dew point smaller than any day in zip code 94107, and in which zip codes were those measurements taken?</question>
[SQL]:
| <SQL_QUERY>SELECT date , zip_code FROM weather WHERE min_dew_point_f < (SELECT min(min_dew_point_f) FROM weather WHERE zip_code = 94107)</SQL_QUERY> | bike_1 | SELECT date , zip_code FROM weather WHERE min_dew_point_f < (SELECT min(min_dew_point_f) FROM weather WHERE zip_code = 94107) | Which days had a minimum dew point smaller than any day in zip code 94107, and in which zip codes were those measurements taken? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each trip, return its ending station's installation date.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.id , T2.installation_date FROM trip AS T1 JOIN station AS T2 ON T1.end_station_id = T2.id</SQL_QUERY> | bike_1 | SELECT T1.id , T2.installation_date FROM trip AS T1 JOIN station AS T2 ON T1.end_station_id = T2.id | For each trip, return its ending station's installation date. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the installation date for each ending station on all the trips?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.id , T2.installation_date FROM trip AS T1 JOIN station AS T2 ON T1.end_station_id = T2.id</SQL_QUERY> | bike_1 | SELECT T1.id , T2.installation_date FROM trip AS T1 JOIN station AS T2 ON T1.end_station_id = T2.id | What is the installation date for each ending station on all the trips? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Which trip started from the station with the largest dock count? Give me the trip id.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.id FROM trip AS T1 JOIN station AS T2 ON T1.start_station_id = T2.id ORDER BY T2.dock_count DESC LIMIT 1</SQL_QUERY> | bike_1 | SELECT T1.id FROM trip AS T1 JOIN station AS T2 ON T1.start_station_id = T2.id ORDER BY T2.dock_count DESC LIMIT 1 | Which trip started from the station with the largest dock count? Give me the trip id. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the id of the trip that started from the station with the highest dock count?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.id FROM trip AS T1 JOIN station AS T2 ON T1.start_station_id = T2.id ORDER BY T2.dock_count DESC LIMIT 1</SQL_QUERY> | bike_1 | SELECT T1.id FROM trip AS T1 JOIN station AS T2 ON T1.start_station_id = T2.id ORDER BY T2.dock_count DESC LIMIT 1 | What is the id of the trip that started from the station with the highest dock count? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Count the number of trips that did not end in San Francisco city.</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM trip AS T1 JOIN station AS T2 ON T1.end_station_id = T2.id WHERE T2.city != "San Francisco"</SQL_QUERY> | bike_1 | SELECT count(*) FROM trip AS T1 JOIN station AS T2 ON T1.end_station_id = T2.id WHERE T2.city != "San Francisco" | Count the number of trips that did not end in San Francisco city. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>How many trips did not end in San Francisco?</question>
[SQL]:
| <SQL_QUERY>SELECT count(*) FROM trip AS T1 JOIN station AS T2 ON T1.end_station_id = T2.id WHERE T2.city != "San Francisco"</SQL_QUERY> | bike_1 | SELECT count(*) FROM trip AS T1 JOIN station AS T2 ON T1.end_station_id = T2.id WHERE T2.city != "San Francisco" | How many trips did not end in San Francisco? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>In zip code 94107, on which day neither Fog nor Rain was not observed?</question>
[SQL]:
| <SQL_QUERY>SELECT date FROM weather WHERE zip_code = 94107 AND EVENTS != "Fog" AND EVENTS != "Rain"</SQL_QUERY> | bike_1 | SELECT date FROM weather WHERE zip_code = 94107 AND EVENTS != "Fog" AND EVENTS != "Rain" | In zip code 94107, on which day neither Fog nor Rain was not observed? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>On which day has it neither been foggy nor rained in the zip code of 94107?</question>
[SQL]:
| <SQL_QUERY>SELECT date FROM weather WHERE zip_code = 94107 AND EVENTS != "Fog" AND EVENTS != "Rain"</SQL_QUERY> | bike_1 | SELECT date FROM weather WHERE zip_code = 94107 AND EVENTS != "Fog" AND EVENTS != "Rain" | On which day has it neither been foggy nor rained in the zip code of 94107? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the ids of stations that have latitude above 37.4 and never had bike availability below 7?</question>
[SQL]:
| <SQL_QUERY>SELECT id FROM station WHERE lat > 37.4 EXCEPT SELECT station_id FROM status GROUP BY station_id HAVING min(bikes_available) < 7</SQL_QUERY> | bike_1 | SELECT id FROM station WHERE lat > 37.4 EXCEPT SELECT station_id FROM status GROUP BY station_id HAVING min(bikes_available) < 7 | What are the ids of stations that have latitude above 37.4 and never had bike availability below 7? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the ids of all stations that have a latitude above 37.4 and have never had less than 7 bikes available?</question>
[SQL]:
| <SQL_QUERY>SELECT id FROM station WHERE lat > 37.4 EXCEPT SELECT station_id FROM status GROUP BY station_id HAVING min(bikes_available) < 7</SQL_QUERY> | bike_1 | SELECT id FROM station WHERE lat > 37.4 EXCEPT SELECT station_id FROM status GROUP BY station_id HAVING min(bikes_available) < 7 | What are the ids of all stations that have a latitude above 37.4 and have never had less than 7 bikes available? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are names of stations that have average bike availability above 10 and are not located in San Jose city?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id GROUP BY T2.station_id HAVING avg(bikes_available) > 10 EXCEPT SELECT name FROM station WHERE city = "San Jose"</SQL_QUERY> | bike_1 | SELECT T1.name FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id GROUP BY T2.station_id HAVING avg(bikes_available) > 10 EXCEPT SELECT name FROM station WHERE city = "San Jose" | What are names of stations that have average bike availability above 10 and are not located in San Jose city? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the names of all stations that have more than 10 bikes available and are not located in San Jose?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id GROUP BY T2.station_id HAVING avg(bikes_available) > 10 EXCEPT SELECT name FROM station WHERE city = "San Jose"</SQL_QUERY> | bike_1 | SELECT T1.name FROM station AS T1 JOIN status AS T2 ON T1.id = T2.station_id GROUP BY T2.station_id HAVING avg(bikes_available) > 10 EXCEPT SELECT name FROM station WHERE city = "San Jose" | What are the names of all stations that have more than 10 bikes available and are not located in San Jose? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the name, latitude, and city of the station with the lowest latitude?</question>
[SQL]:
| <SQL_QUERY>SELECT name , lat , city FROM station ORDER BY lat LIMIT 1</SQL_QUERY> | bike_1 | SELECT name , lat , city FROM station ORDER BY lat LIMIT 1 | What are the name, latitude, and city of the station with the lowest latitude? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name, latitude, and city of the station that is located the furthest South?</question>
[SQL]:
| <SQL_QUERY>SELECT name , lat , city FROM station ORDER BY lat LIMIT 1</SQL_QUERY> | bike_1 | SELECT name , lat , city FROM station ORDER BY lat LIMIT 1 | What is the name, latitude, and city of the station that is located the furthest South? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the date, mean temperature and mean humidity for the top 3 days with the largest max gust speeds?</question>
[SQL]:
| <SQL_QUERY>SELECT date , mean_temperature_f , mean_humidity FROM weather ORDER BY max_gust_speed_mph DESC LIMIT 3</SQL_QUERY> | bike_1 | SELECT date , mean_temperature_f , mean_humidity FROM weather ORDER BY max_gust_speed_mph DESC LIMIT 3 | What are the date, mean temperature and mean humidity for the top 3 days with the largest max gust speeds? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the date, average temperature and mean humidity for the days with the 3 largest maximum gust speeds?</question>
[SQL]:
| <SQL_QUERY>SELECT date , mean_temperature_f , mean_humidity FROM weather ORDER BY max_gust_speed_mph DESC LIMIT 3</SQL_QUERY> | bike_1 | SELECT date , mean_temperature_f , mean_humidity FROM weather ORDER BY max_gust_speed_mph DESC LIMIT 3 | What is the date, average temperature and mean humidity for the days with the 3 largest maximum gust speeds? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List the name and the number of stations for all the cities that have at least 15 stations.</question>
[SQL]:
| <SQL_QUERY>SELECT city , COUNT(*) FROM station GROUP BY city HAVING COUNT(*) >= 15</SQL_QUERY> | bike_1 | SELECT city , COUNT(*) FROM station GROUP BY city HAVING COUNT(*) >= 15 | List the name and the number of stations for all the cities that have at least 15 stations. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What is the name of every city that has at least 15 stations and how many stations does it have?</question>
[SQL]:
| <SQL_QUERY>SELECT city , COUNT(*) FROM station GROUP BY city HAVING COUNT(*) >= 15</SQL_QUERY> | bike_1 | SELECT city , COUNT(*) FROM station GROUP BY city HAVING COUNT(*) >= 15 | What is the name of every city that has at least 15 stations and how many stations does it have? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the ids and names of stations from which at least 200 trips started.</question>
[SQL]:
| <SQL_QUERY>SELECT start_station_id , start_station_name FROM trip GROUP BY start_station_name HAVING COUNT(*) >= 200</SQL_QUERY> | bike_1 | SELECT start_station_id , start_station_name FROM trip GROUP BY start_station_name HAVING COUNT(*) >= 200 | Find the ids and names of stations from which at least 200 trips started. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the ids and names of all start stations that were the beginning of at least 200 trips?</question>
[SQL]:
| <SQL_QUERY>SELECT start_station_id , start_station_name FROM trip GROUP BY start_station_name HAVING COUNT(*) >= 200</SQL_QUERY> | bike_1 | SELECT start_station_id , start_station_name FROM trip GROUP BY start_station_name HAVING COUNT(*) >= 200 | What are the ids and names of all start stations that were the beginning of at least 200 trips? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the zip code in which the average mean visibility is lower than 10.</question>
[SQL]:
| <SQL_QUERY>SELECT zip_code FROM weather GROUP BY zip_code HAVING avg(mean_visibility_miles) < 10</SQL_QUERY> | bike_1 | SELECT zip_code FROM weather GROUP BY zip_code HAVING avg(mean_visibility_miles) < 10 | Find the zip code in which the average mean visibility is lower than 10. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each zip code, select all those that have an average mean visiblity below 10.</question>
[SQL]:
| <SQL_QUERY>SELECT zip_code FROM weather GROUP BY zip_code HAVING avg(mean_visibility_miles) < 10</SQL_QUERY> | bike_1 | SELECT zip_code FROM weather GROUP BY zip_code HAVING avg(mean_visibility_miles) < 10 | For each zip code, select all those that have an average mean visiblity below 10. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List all the cities in a decreasing order of each city's stations' highest latitude.</question>
[SQL]:
| <SQL_QUERY>SELECT city FROM station GROUP BY city ORDER BY max(lat) DESC</SQL_QUERY> | bike_1 | SELECT city FROM station GROUP BY city ORDER BY max(lat) DESC | List all the cities in a decreasing order of each city's stations' highest latitude. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each city, list their names in decreasing order by their highest station latitude.</question>
[SQL]:
| <SQL_QUERY>SELECT city FROM station GROUP BY city ORDER BY max(lat) DESC</SQL_QUERY> | bike_1 | SELECT city FROM station GROUP BY city ORDER BY max(lat) DESC | For each city, list their names in decreasing order by their highest station latitude. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the dates that had the top 5 cloud cover rates? Also tell me the cloud cover rate.</question>
[SQL]:
| <SQL_QUERY>SELECT date , cloud_cover FROM weather ORDER BY cloud_cover DESC LIMIT 5</SQL_QUERY> | bike_1 | SELECT date , cloud_cover FROM weather ORDER BY cloud_cover DESC LIMIT 5 | What are the dates that had the top 5 cloud cover rates? Also tell me the cloud cover rate. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the dates that have the 5 highest cloud cover rates and what are the rates?</question>
[SQL]:
| <SQL_QUERY>SELECT date , cloud_cover FROM weather ORDER BY cloud_cover DESC LIMIT 5</SQL_QUERY> | bike_1 | SELECT date , cloud_cover FROM weather ORDER BY cloud_cover DESC LIMIT 5 | What are the dates that have the 5 highest cloud cover rates and what are the rates? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the ids and durations of the trips with the top 3 durations?</question>
[SQL]:
| <SQL_QUERY>SELECT id , duration FROM trip ORDER BY duration DESC LIMIT 3</SQL_QUERY> | bike_1 | SELECT id , duration FROM trip ORDER BY duration DESC LIMIT 3 | What are the ids and durations of the trips with the top 3 durations? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the ids of the trips that lasted the longest and how long did they last?</question>
[SQL]:
| <SQL_QUERY>SELECT id , duration FROM trip ORDER BY duration DESC LIMIT 3</SQL_QUERY> | bike_1 | SELECT id , duration FROM trip ORDER BY duration DESC LIMIT 3 | What are the ids of the trips that lasted the longest and how long did they last? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each station, return its longitude and the average duration of trips that started from the station.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , T1.long , avg(T2.duration) FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.start_station_id GROUP BY T2.start_station_id</SQL_QUERY> | bike_1 | SELECT T1.name , T1.long , avg(T2.duration) FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.start_station_id GROUP BY T2.start_station_id | For each station, return its longitude and the average duration of trips that started from the station. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each start station id, what is its name, longitude and average duration of trips started there?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , T1.long , avg(T2.duration) FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.start_station_id GROUP BY T2.start_station_id</SQL_QUERY> | bike_1 | SELECT T1.name , T1.long , avg(T2.duration) FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.start_station_id GROUP BY T2.start_station_id | For each start station id, what is its name, longitude and average duration of trips started there? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each station, find its latitude and the minimum duration of trips that ended at the station.</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , T1.lat , min(T2.duration) FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.end_station_id GROUP BY T2.end_station_id</SQL_QUERY> | bike_1 | SELECT T1.name , T1.lat , min(T2.duration) FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.end_station_id GROUP BY T2.end_station_id | For each station, find its latitude and the minimum duration of trips that ended at the station. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>For each end station id, what is its name, latitude, and minimum duration for trips ended there?</question>
[SQL]:
| <SQL_QUERY>SELECT T1.name , T1.lat , min(T2.duration) FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.end_station_id GROUP BY T2.end_station_id</SQL_QUERY> | bike_1 | SELECT T1.name , T1.lat , min(T2.duration) FROM station AS T1 JOIN trip AS T2 ON T1.id = T2.end_station_id GROUP BY T2.end_station_id | For each end station id, what is its name, latitude, and minimum duration for trips ended there? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>List all the distinct stations from which a trip of duration below 100 started.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT start_station_name FROM trip WHERE duration < 100</SQL_QUERY> | bike_1 | SELECT DISTINCT start_station_name FROM trip WHERE duration < 100 | List all the distinct stations from which a trip of duration below 100 started. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are all the different start station names for a trip that lasted less than 100?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT start_station_name FROM trip WHERE duration < 100</SQL_QUERY> | bike_1 | SELECT DISTINCT start_station_name FROM trip WHERE duration < 100 | What are all the different start station names for a trip that lasted less than 100? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find all the zip codes in which the max dew point have never reached 70.</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT zip_code FROM weather EXCEPT SELECT DISTINCT zip_code FROM weather WHERE max_dew_point_f >= 70</SQL_QUERY> | bike_1 | SELECT DISTINCT zip_code FROM weather EXCEPT SELECT DISTINCT zip_code FROM weather WHERE max_dew_point_f >= 70 | Find all the zip codes in which the max dew point have never reached 70. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are all the different zip codes that have a maximum dew point that was always below 70?</question>
[SQL]:
| <SQL_QUERY>SELECT DISTINCT zip_code FROM weather EXCEPT SELECT DISTINCT zip_code FROM weather WHERE max_dew_point_f >= 70</SQL_QUERY> | bike_1 | SELECT DISTINCT zip_code FROM weather EXCEPT SELECT DISTINCT zip_code FROM weather WHERE max_dew_point_f >= 70 | What are all the different zip codes that have a maximum dew point that was always below 70? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>Find the id for the trips that lasted at least as long as the average duration of trips in zip code 94103.</question>
[SQL]:
| <SQL_QUERY>SELECT id FROM trip WHERE duration >= (SELECT avg(duration) FROM trip WHERE zip_code = 94103)</SQL_QUERY> | bike_1 | SELECT id FROM trip WHERE duration >= (SELECT avg(duration) FROM trip WHERE zip_code = 94103) | Find the id for the trips that lasted at least as long as the average duration of trips in zip code 94103. | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the ids of all trips that had a duration as long as the average trip duration in the zip code 94103?</question>
[SQL]:
| <SQL_QUERY>SELECT id FROM trip WHERE duration >= (SELECT avg(duration) FROM trip WHERE zip_code = 94103)</SQL_QUERY> | bike_1 | SELECT id FROM trip WHERE duration >= (SELECT avg(duration) FROM trip WHERE zip_code = 94103) | What are the ids of all trips that had a duration as long as the average trip duration in the zip code 94103? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |
This is a task converting text into SQL statements. We will first give the dataset schema and column types, primary keys and foreign keys and then ask a question in text. You are asked to generate SQL statement in SQLite.
<schema>[Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text);</schema>"
<primary_keys>[Primary Keys]: station : id, status : id</primary_keys>"
<foreign_keys>[Foreign Keys]: status : station_id = station : id</foreign_keys>"
Answer the following question with a SQL Statement:<question>What are the dates in which the mean sea level pressure was between 30.3 and 31?</question>
[SQL]:
| <SQL_QUERY>SELECT date FROM weather WHERE mean_sea_level_pressure_inches BETWEEN 30.3 AND 31</SQL_QUERY> | bike_1 | SELECT date FROM weather WHERE mean_sea_level_pressure_inches BETWEEN 30.3 AND 31 | What are the dates in which the mean sea level pressure was between 30.3 and 31? | [Schema (values) (types)]: | bike_1 | station : id (text) , name (number) , lat (text) , long (number) , dock_count (number) , city (number) , installation_date (text) | status : station_id (text) , bikes_available (number) , docks_available (text) , time (number) | trip : id (text) , duration (number) , start_date (text) , start_station_name (number) , start_station_id (number) , end_date (number) , end_station_name (text) , end_station_id (text) , bike_id (number) , subscription_type (number) , zip_code (number) | weather : date (text) , max_temperature_f (number) , mean_temperature_f (text) , min_temperature_f (number) , max_dew_point_f (number) , mean_dew_point_f (number) , min_dew_point_f (text) , max_humidity (text) , mean_humidity (number) , min_humidity (number) , max_sea_level_pressure_inches (number) , mean_sea_level_pressure_inches (text) , min_sea_level_pressure_inches (number) , max_visibility_miles (number) , mean_visibility_miles (text) , min_visibility_miles (text) , max_wind_speed_mph (number) , mean_wind_speed_mph (text) , max_gust_speed_mph (text) , precipitation_inches (number) , cloud_cover (number) , events (text) , wind_dir_degrees (number) , zip_code (text); | [Primary Keys]: station : id, status : id | [Foreign Keys]: status : station_id = station : id |