QIAN-ME/bird_schema_data huggingface dataset:
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 software_company
【Schema】
# Table: Customers
[
(ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(SEX:TEXT, Examples: [Male, Female]),
(MARITAL_STATUS:TEXT, Examples: [Never-married, Married-civ-spouse, Divorced]),
(GEOID:INTEGER, Examples: [61, 70, 53]),
(EDUCATIONNUM:INTEGER, Examples: [7, 3, 4]),
(OCCUPATION:TEXT, Examples: [Machine-op-inspct, Handlers-cleaners, Exec-managerial]),
(age:INTEGER, Examples: [62, 78, 69])
]
# Table: Mailings1_2
[
(REFID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(REF_DATE:DATETIME, Examples: [2007-02-01 12:00:00]),
(RESPONSE:TEXT, Examples: [false, true])
]
# Table: mailings3
[
(REFID:INTEGER, Primary Key, Examples: [60000, 60001, 60002]),
(REF_DATE:DATETIME, Examples: [2007-07-01 12:00:00]),
(RESPONSE:TEXT, Examples: [false, true])
]
# Table: Demog
[
(GEOID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(INHABITANTS_K:REAL, Examples: [30.046, 36.25, 47.645]),
(INCOME_K:REAL, Examples: [2631.47, 3012.75, 2192.41]),
(A_VAR1:REAL, Examples: [6.084, 4.604, 4.911]),
(A_VAR2:REAL, Examples: [5.79, 8.309, 8.557]),
(A_VAR3:REAL, Examples: [8.595, 6.007, 5.934]),
(A_VAR4:REAL, Examples: [3.935, 5.938, 6.494]),
(A_VAR5:REAL, Examples: [6.362, 8.773, 9.172]),
(A_VAR6:REAL, Examples: [8.626, 3.579, 3.202]),
(A_VAR7:REAL, Examples: [4.624, 6.349, 6.157]),
(A_VAR8:REAL, Examples: [8.324, 4.694, 4.822]),
(A_VAR9:REAL, Examples: [5.233, 6.884, 7.942]),
(A_VAR10:REAL, Examples: [6.232, 7.062, 7.901]),
(A_VAR11:REAL, Examples: [5.205, 7.319, 7.928]),
(A_VAR12:REAL, Examples: [8.231, 3.72, 2.33]),
(A_VAR13:REAL, Examples: [6.746, 6.405, 6.029]),
(A_VAR14:REAL, Examples: [8.679, 7.202, 6.455]),
(A_VAR15:REAL, Examples: [5.292, 4.932, 4.72]),
(A_VAR16:REAL, Examples: [3.5, 7.969, 8.564]),
(A_VAR17:REAL, Examples: [5.512, 8.15, 8.342]),
(A_VAR18:REAL, Examples: [5.783, 5.633, 4.938])
]
# Table: Sales
[
(EVENTID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(REFID:INTEGER, Examples: [0, 1, 2]),
(EVENT_DATE:DATETIME, Examples: [2006-12-21 12:00:00]),
(AMOUNT:REAL, Examples: [17.907, 17.401, 13.277])
]
【Foreign keys】
Customers.GEOID=Demog.GEOID
Mailings1_2.REFID=Customers.ID
Sales.REFID=Customers.ID

    【Question】
    What percentage of elderly customers who are never married in the place with geographic ID 24? elderly customers refer to age > 65; DIVIDE(COUNT(ID where age > 65, MARITAL_STATUS = 'never married' and GEOID = 24), COUNT(ID where GEOID = 24)) as percentage;

    【Evidence】
    elderly customers refer to age > 65; DIVIDE(COUNT(ID where age > 65, MARITAL_STATUS = 'never married' and GEOID = 24), COUNT(ID where GEOID = 24)) as percentage;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT CAST(SUM(CASE WHEN T1.MARITAL_STATUS = 'never married' THEN 1.0 ELSE 0 END) AS REAL) * 100 / COUNT(*) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T1.GEOID = 24
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 software_company
【Schema】
# Table: Customers
[
(ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(SEX:TEXT, Examples: [Male, Female]),
(MARITAL_STATUS:TEXT, Examples: [Never-married, Married-civ-spouse, Divorced]),
(GEOID:INTEGER, Examples: [61, 70, 53]),
(EDUCATIONNUM:INTEGER, Examples: [7, 3, 4]),
(OCCUPATION:TEXT, Examples: [Machine-op-inspct, Handlers-cleaners, Exec-managerial]),
(age:INTEGER, Examples: [62, 78, 69])
]
# Table: Mailings1_2
[
(REFID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(REF_DATE:DATETIME, Examples: [2007-02-01 12:00:00]),
(RESPONSE:TEXT, Examples: [false, true])
]
# Table: mailings3
[
(REFID:INTEGER, Primary Key, Examples: [60000, 60001, 60002]),
(REF_DATE:DATETIME, Examples: [2007-07-01 12:00:00]),
(RESPONSE:TEXT, Examples: [false, true])
]
# Table: Demog
[
(GEOID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(INHABITANTS_K:REAL, Examples: [30.046, 36.25, 47.645]),
(INCOME_K:REAL, Examples: [2631.47, 3012.75, 2192.41]),
(A_VAR1:REAL, Examples: [6.084, 4.604, 4.911]),
(A_VAR2:REAL, Examples: [5.79, 8.309, 8.557]),
(A_VAR3:REAL, Examples: [8.595, 6.007, 5.934]),
(A_VAR4:REAL, Examples: [3.935, 5.938, 6.494]),
(A_VAR5:REAL, Examples: [6.362, 8.773, 9.172]),
(A_VAR6:REAL, Examples: [8.626, 3.579, 3.202]),
(A_VAR7:REAL, Examples: [4.624, 6.349, 6.157]),
(A_VAR8:REAL, Examples: [8.324, 4.694, 4.822]),
(A_VAR9:REAL, Examples: [5.233, 6.884, 7.942]),
(A_VAR10:REAL, Examples: [6.232, 7.062, 7.901]),
(A_VAR11:REAL, Examples: [5.205, 7.319, 7.928]),
(A_VAR12:REAL, Examples: [8.231, 3.72, 2.33]),
(A_VAR13:REAL, Examples: [6.746, 6.405, 6.029]),
(A_VAR14:REAL, Examples: [8.679, 7.202, 6.455]),
(A_VAR15:REAL, Examples: [5.292, 4.932, 4.72]),
(A_VAR16:REAL, Examples: [3.5, 7.969, 8.564]),
(A_VAR17:REAL, Examples: [5.512, 8.15, 8.342]),
(A_VAR18:REAL, Examples: [5.783, 5.633, 4.938])
]
# Table: Sales
[
(EVENTID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(REFID:INTEGER, Examples: [0, 1, 2]),
(EVENT_DATE:DATETIME, Examples: [2006-12-21 12:00:00]),
(AMOUNT:REAL, Examples: [17.907, 17.401, 13.277])
]
【Foreign keys】
Customers.GEOID=Demog.GEOID
Mailings1_2.REFID=Customers.ID
Sales.REFID=Customers.ID

    【Question】
    Among the customers with an average income per inhabitant above 3000, what percentage are in their eighties? average income per inhabitant above 3000 refers to INCOME_K > 3000; eighties refer to age BETWEEN 80 AND 89; DIVIDE(COUNT(INCOME_K > 3000 and age BETWEEN 80 AND 89), COUNT(INCOME_K > 3000 )) as percentage;

    【Evidence】
    average income per inhabitant above 3000 refers to INCOME_K > 3000; eighties refer to age BETWEEN 80 AND 89; DIVIDE(COUNT(INCOME_K > 3000 and age BETWEEN 80 AND 89), COUNT(INCOME_K > 3000 )) as percentage;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT CAST(SUM(CASE WHEN T1.age BETWEEN 80 AND 89 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.ID) FROM Customers AS T1 INNER JOIN Demog AS T2 ON T1.GEOID = T2.GEOID WHERE T2.INCOME_K > 3000
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 software_company
【Schema】
# Table: Customers
[
(ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(SEX:TEXT, Examples: [Male, Female]),
(MARITAL_STATUS:TEXT, Examples: [Never-married, Married-civ-spouse, Divorced]),
(GEOID:INTEGER, Examples: [61, 70, 53]),
(EDUCATIONNUM:INTEGER, Examples: [7, 3, 4]),
(OCCUPATION:TEXT, Examples: [Machine-op-inspct, Handlers-cleaners, Exec-managerial]),
(age:INTEGER, Examples: [62, 78, 69])
]
# Table: Mailings1_2
[
(REFID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(REF_DATE:DATETIME, Examples: [2007-02-01 12:00:00]),
(RESPONSE:TEXT, Examples: [false, true])
]
# Table: mailings3
[
(REFID:INTEGER, Primary Key, Examples: [60000, 60001, 60002]),
(REF_DATE:DATETIME, Examples: [2007-07-01 12:00:00]),
(RESPONSE:TEXT, Examples: [false, true])
]
# Table: Demog
[
(GEOID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(INHABITANTS_K:REAL, Examples: [30.046, 36.25, 47.645]),
(INCOME_K:REAL, Examples: [2631.47, 3012.75, 2192.41]),
(A_VAR1:REAL, Examples: [6.084, 4.604, 4.911]),
(A_VAR2:REAL, Examples: [5.79, 8.309, 8.557]),
(A_VAR3:REAL, Examples: [8.595, 6.007, 5.934]),
(A_VAR4:REAL, Examples: [3.935, 5.938, 6.494]),
(A_VAR5:REAL, Examples: [6.362, 8.773, 9.172]),
(A_VAR6:REAL, Examples: [8.626, 3.579, 3.202]),
(A_VAR7:REAL, Examples: [4.624, 6.349, 6.157]),
(A_VAR8:REAL, Examples: [8.324, 4.694, 4.822]),
(A_VAR9:REAL, Examples: [5.233, 6.884, 7.942]),
(A_VAR10:REAL, Examples: [6.232, 7.062, 7.901]),
(A_VAR11:REAL, Examples: [5.205, 7.319, 7.928]),
(A_VAR12:REAL, Examples: [8.231, 3.72, 2.33]),
(A_VAR13:REAL, Examples: [6.746, 6.405, 6.029]),
(A_VAR14:REAL, Examples: [8.679, 7.202, 6.455]),
(A_VAR15:REAL, Examples: [5.292, 4.932, 4.72]),
(A_VAR16:REAL, Examples: [3.5, 7.969, 8.564]),
(A_VAR17:REAL, Examples: [5.512, 8.15, 8.342]),
(A_VAR18:REAL, Examples: [5.783, 5.633, 4.938])
]
# Table: Sales
[
(EVENTID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(REFID:INTEGER, Examples: [0, 1, 2]),
(EVENT_DATE:DATETIME, Examples: [2006-12-21 12:00:00]),
(AMOUNT:REAL, Examples: [17.907, 17.401, 13.277])
]
【Foreign keys】
Customers.GEOID=Demog.GEOID
Mailings1_2.REFID=Customers.ID
Sales.REFID=Customers.ID

    【Question】
    How many of the customer's reference ID that has a TRUE response? reference ID refers to REFID;

    【Evidence】
    reference ID refers to REFID;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT COUNT(REFID) FROM Mailings1_2 WHERE RESPONSE = 'true'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 software_company
【Schema】
# Table: Customers
[
(ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(SEX:TEXT, Examples: [Male, Female]),
(MARITAL_STATUS:TEXT, Examples: [Never-married, Married-civ-spouse, Divorced]),
(GEOID:INTEGER, Examples: [61, 70, 53]),
(EDUCATIONNUM:INTEGER, Examples: [7, 3, 4]),
(OCCUPATION:TEXT, Examples: [Machine-op-inspct, Handlers-cleaners, Exec-managerial]),
(age:INTEGER, Examples: [62, 78, 69])
]
# Table: Mailings1_2
[
(REFID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(REF_DATE:DATETIME, Examples: [2007-02-01 12:00:00]),
(RESPONSE:TEXT, Examples: [false, true])
]
# Table: mailings3
[
(REFID:INTEGER, Primary Key, Examples: [60000, 60001, 60002]),
(REF_DATE:DATETIME, Examples: [2007-07-01 12:00:00]),
(RESPONSE:TEXT, Examples: [false, true])
]
# Table: Demog
[
(GEOID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(INHABITANTS_K:REAL, Examples: [30.046, 36.25, 47.645]),
(INCOME_K:REAL, Examples: [2631.47, 3012.75, 2192.41]),
(A_VAR1:REAL, Examples: [6.084, 4.604, 4.911]),
(A_VAR2:REAL, Examples: [5.79, 8.309, 8.557]),
(A_VAR3:REAL, Examples: [8.595, 6.007, 5.934]),
(A_VAR4:REAL, Examples: [3.935, 5.938, 6.494]),
(A_VAR5:REAL, Examples: [6.362, 8.773, 9.172]),
(A_VAR6:REAL, Examples: [8.626, 3.579, 3.202]),
(A_VAR7:REAL, Examples: [4.624, 6.349, 6.157]),
(A_VAR8:REAL, Examples: [8.324, 4.694, 4.822]),
(A_VAR9:REAL, Examples: [5.233, 6.884, 7.942]),
(A_VAR10:REAL, Examples: [6.232, 7.062, 7.901]),
(A_VAR11:REAL, Examples: [5.205, 7.319, 7.928]),
(A_VAR12:REAL, Examples: [8.231, 3.72, 2.33]),
(A_VAR13:REAL, Examples: [6.746, 6.405, 6.029]),
(A_VAR14:REAL, Examples: [8.679, 7.202, 6.455]),
(A_VAR15:REAL, Examples: [5.292, 4.932, 4.72]),
(A_VAR16:REAL, Examples: [3.5, 7.969, 8.564]),
(A_VAR17:REAL, Examples: [5.512, 8.15, 8.342]),
(A_VAR18:REAL, Examples: [5.783, 5.633, 4.938])
]
# Table: Sales
[
(EVENTID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(REFID:INTEGER, Examples: [0, 1, 2]),
(EVENT_DATE:DATETIME, Examples: [2006-12-21 12:00:00]),
(AMOUNT:REAL, Examples: [17.907, 17.401, 13.277])
]
【Foreign keys】
Customers.GEOID=Demog.GEOID
Mailings1_2.REFID=Customers.ID
Sales.REFID=Customers.ID

    【Question】
    List down the customer's reference ID with true response. reference ID refers to REFID;

    【Evidence】
    reference ID refers to REFID;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT REFID FROM Mailings1_2 WHERE RESPONSE = 'true'
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 software_company
【Schema】
# Table: Customers
[
(ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(SEX:TEXT, Examples: [Male, Female]),
(MARITAL_STATUS:TEXT, Examples: [Never-married, Married-civ-spouse, Divorced]),
(GEOID:INTEGER, Examples: [61, 70, 53]),
(EDUCATIONNUM:INTEGER, Examples: [7, 3, 4]),
(OCCUPATION:TEXT, Examples: [Machine-op-inspct, Handlers-cleaners, Exec-managerial]),
(age:INTEGER, Examples: [62, 78, 69])
]
# Table: Mailings1_2
[
(REFID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(REF_DATE:DATETIME, Examples: [2007-02-01 12:00:00]),
(RESPONSE:TEXT, Examples: [false, true])
]
# Table: mailings3
[
(REFID:INTEGER, Primary Key, Examples: [60000, 60001, 60002]),
(REF_DATE:DATETIME, Examples: [2007-07-01 12:00:00]),
(RESPONSE:TEXT, Examples: [false, true])
]
# Table: Demog
[
(GEOID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(INHABITANTS_K:REAL, Examples: [30.046, 36.25, 47.645]),
(INCOME_K:REAL, Examples: [2631.47, 3012.75, 2192.41]),
(A_VAR1:REAL, Examples: [6.084, 4.604, 4.911]),
(A_VAR2:REAL, Examples: [5.79, 8.309, 8.557]),
(A_VAR3:REAL, Examples: [8.595, 6.007, 5.934]),
(A_VAR4:REAL, Examples: [3.935, 5.938, 6.494]),
(A_VAR5:REAL, Examples: [6.362, 8.773, 9.172]),
(A_VAR6:REAL, Examples: [8.626, 3.579, 3.202]),
(A_VAR7:REAL, Examples: [4.624, 6.349, 6.157]),
(A_VAR8:REAL, Examples: [8.324, 4.694, 4.822]),
(A_VAR9:REAL, Examples: [5.233, 6.884, 7.942]),
(A_VAR10:REAL, Examples: [6.232, 7.062, 7.901]),
(A_VAR11:REAL, Examples: [5.205, 7.319, 7.928]),
(A_VAR12:REAL, Examples: [8.231, 3.72, 2.33]),
(A_VAR13:REAL, Examples: [6.746, 6.405, 6.029]),
(A_VAR14:REAL, Examples: [8.679, 7.202, 6.455]),
(A_VAR15:REAL, Examples: [5.292, 4.932, 4.72]),
(A_VAR16:REAL, Examples: [3.5, 7.969, 8.564]),
(A_VAR17:REAL, Examples: [5.512, 8.15, 8.342]),
(A_VAR18:REAL, Examples: [5.783, 5.633, 4.938])
]
# Table: Sales
[
(EVENTID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(REFID:INTEGER, Examples: [0, 1, 2]),
(EVENT_DATE:DATETIME, Examples: [2006-12-21 12:00:00]),
(AMOUNT:REAL, Examples: [17.907, 17.401, 13.277])
]
【Foreign keys】
Customers.GEOID=Demog.GEOID
Mailings1_2.REFID=Customers.ID
Sales.REFID=Customers.ID

    【Question】
    What is the total number of widowed customers with an age below 50? widowed customers with an age below 50 refer to MARITAL_STATUS = 'Widowed' where age < 50;

    【Evidence】
    widowed customers with an age below 50 refer to MARITAL_STATUS = 'Widowed' where age < 50;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT COUNT(ID) FROM Customers WHERE MARITAL_STATUS = 'Widowed' AND age < 50
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 software_company
【Schema】
# Table: Customers
[
(ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(SEX:TEXT, Examples: [Male, Female]),
(MARITAL_STATUS:TEXT, Examples: [Never-married, Married-civ-spouse, Divorced]),
(GEOID:INTEGER, Examples: [61, 70, 53]),
(EDUCATIONNUM:INTEGER, Examples: [7, 3, 4]),
(OCCUPATION:TEXT, Examples: [Machine-op-inspct, Handlers-cleaners, Exec-managerial]),
(age:INTEGER, Examples: [62, 78, 69])
]
# Table: Mailings1_2
[
(REFID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(REF_DATE:DATETIME, Examples: [2007-02-01 12:00:00]),
(RESPONSE:TEXT, Examples: [false, true])
]
# Table: mailings3
[
(REFID:INTEGER, Primary Key, Examples: [60000, 60001, 60002]),
(REF_DATE:DATETIME, Examples: [2007-07-01 12:00:00]),
(RESPONSE:TEXT, Examples: [false, true])
]
# Table: Demog
[
(GEOID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(INHABITANTS_K:REAL, Examples: [30.046, 36.25, 47.645]),
(INCOME_K:REAL, Examples: [2631.47, 3012.75, 2192.41]),
(A_VAR1:REAL, Examples: [6.084, 4.604, 4.911]),
(A_VAR2:REAL, Examples: [5.79, 8.309, 8.557]),
(A_VAR3:REAL, Examples: [8.595, 6.007, 5.934]),
(A_VAR4:REAL, Examples: [3.935, 5.938, 6.494]),
(A_VAR5:REAL, Examples: [6.362, 8.773, 9.172]),
(A_VAR6:REAL, Examples: [8.626, 3.579, 3.202]),
(A_VAR7:REAL, Examples: [4.624, 6.349, 6.157]),
(A_VAR8:REAL, Examples: [8.324, 4.694, 4.822]),
(A_VAR9:REAL, Examples: [5.233, 6.884, 7.942]),
(A_VAR10:REAL, Examples: [6.232, 7.062, 7.901]),
(A_VAR11:REAL, Examples: [5.205, 7.319, 7.928]),
(A_VAR12:REAL, Examples: [8.231, 3.72, 2.33]),
(A_VAR13:REAL, Examples: [6.746, 6.405, 6.029]),
(A_VAR14:REAL, Examples: [8.679, 7.202, 6.455]),
(A_VAR15:REAL, Examples: [5.292, 4.932, 4.72]),
(A_VAR16:REAL, Examples: [3.5, 7.969, 8.564]),
(A_VAR17:REAL, Examples: [5.512, 8.15, 8.342]),
(A_VAR18:REAL, Examples: [5.783, 5.633, 4.938])
]
# Table: Sales
[
(EVENTID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(REFID:INTEGER, Examples: [0, 1, 2]),
(EVENT_DATE:DATETIME, Examples: [2006-12-21 12:00:00]),
(AMOUNT:REAL, Examples: [17.907, 17.401, 13.277])
]
【Foreign keys】
Customers.GEOID=Demog.GEOID
Mailings1_2.REFID=Customers.ID
Sales.REFID=Customers.ID

    【Question】
    List down the geographic identifier with an number of inhabitants less than 30. geographic identifier with an number of inhabitants less than 30 refers to GEOID where INHABITANTS_K < 30;

    【Evidence】
    geographic identifier with an number of inhabitants less than 30 refers to GEOID where INHABITANTS_K < 30;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT GEOID FROM Demog WHERE INHABITANTS_K < 30
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 software_company
【Schema】
# Table: Customers
[
(ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(SEX:TEXT, Examples: [Male, Female]),
(MARITAL_STATUS:TEXT, Examples: [Never-married, Married-civ-spouse, Divorced]),
(GEOID:INTEGER, Examples: [61, 70, 53]),
(EDUCATIONNUM:INTEGER, Examples: [7, 3, 4]),
(OCCUPATION:TEXT, Examples: [Machine-op-inspct, Handlers-cleaners, Exec-managerial]),
(age:INTEGER, Examples: [62, 78, 69])
]
# Table: Mailings1_2
[
(REFID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(REF_DATE:DATETIME, Examples: [2007-02-01 12:00:00]),
(RESPONSE:TEXT, Examples: [false, true])
]
# Table: mailings3
[
(REFID:INTEGER, Primary Key, Examples: [60000, 60001, 60002]),
(REF_DATE:DATETIME, Examples: [2007-07-01 12:00:00]),
(RESPONSE:TEXT, Examples: [false, true])
]
# Table: Demog
[
(GEOID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(INHABITANTS_K:REAL, Examples: [30.046, 36.25, 47.645]),
(INCOME_K:REAL, Examples: [2631.47, 3012.75, 2192.41]),
(A_VAR1:REAL, Examples: [6.084, 4.604, 4.911]),
(A_VAR2:REAL, Examples: [5.79, 8.309, 8.557]),
(A_VAR3:REAL, Examples: [8.595, 6.007, 5.934]),
(A_VAR4:REAL, Examples: [3.935, 5.938, 6.494]),
(A_VAR5:REAL, Examples: [6.362, 8.773, 9.172]),
(A_VAR6:REAL, Examples: [8.626, 3.579, 3.202]),
(A_VAR7:REAL, Examples: [4.624, 6.349, 6.157]),
(A_VAR8:REAL, Examples: [8.324, 4.694, 4.822]),
(A_VAR9:REAL, Examples: [5.233, 6.884, 7.942]),
(A_VAR10:REAL, Examples: [6.232, 7.062, 7.901]),
(A_VAR11:REAL, Examples: [5.205, 7.319, 7.928]),
(A_VAR12:REAL, Examples: [8.231, 3.72, 2.33]),
(A_VAR13:REAL, Examples: [6.746, 6.405, 6.029]),
(A_VAR14:REAL, Examples: [8.679, 7.202, 6.455]),
(A_VAR15:REAL, Examples: [5.292, 4.932, 4.72]),
(A_VAR16:REAL, Examples: [3.5, 7.969, 8.564]),
(A_VAR17:REAL, Examples: [5.512, 8.15, 8.342]),
(A_VAR18:REAL, Examples: [5.783, 5.633, 4.938])
]
# Table: Sales
[
(EVENTID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(REFID:INTEGER, Examples: [0, 1, 2]),
(EVENT_DATE:DATETIME, Examples: [2006-12-21 12:00:00]),
(AMOUNT:REAL, Examples: [17.907, 17.401, 13.277])
]
【Foreign keys】
Customers.GEOID=Demog.GEOID
Mailings1_2.REFID=Customers.ID
Sales.REFID=Customers.ID

    【Question】
    In geographic identifier from 10 to 30, how many of them has an income below 2000? GEOID BETWEEN 10 AND 30; INCOME_K < 2000;

    【Evidence】
    GEOID BETWEEN 10 AND 30; INCOME_K < 2000;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT COUNT(GEOID) FROM Demog WHERE INCOME_K < 2000 AND GEOID >= 10 AND GEOID <= 30
You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 software_company
【Schema】
# Table: Customers
[
(ID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(SEX:TEXT, Examples: [Male, Female]),
(MARITAL_STATUS:TEXT, Examples: [Never-married, Married-civ-spouse, Divorced]),
(GEOID:INTEGER, Examples: [61, 70, 53]),
(EDUCATIONNUM:INTEGER, Examples: [7, 3, 4]),
(OCCUPATION:TEXT, Examples: [Machine-op-inspct, Handlers-cleaners, Exec-managerial]),
(age:INTEGER, Examples: [62, 78, 69])
]
# Table: Mailings1_2
[
(REFID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(REF_DATE:DATETIME, Examples: [2007-02-01 12:00:00]),
(RESPONSE:TEXT, Examples: [false, true])
]
# Table: mailings3
[
(REFID:INTEGER, Primary Key, Examples: [60000, 60001, 60002]),
(REF_DATE:DATETIME, Examples: [2007-07-01 12:00:00]),
(RESPONSE:TEXT, Examples: [false, true])
]
# Table: Demog
[
(GEOID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(INHABITANTS_K:REAL, Examples: [30.046, 36.25, 47.645]),
(INCOME_K:REAL, Examples: [2631.47, 3012.75, 2192.41]),
(A_VAR1:REAL, Examples: [6.084, 4.604, 4.911]),
(A_VAR2:REAL, Examples: [5.79, 8.309, 8.557]),
(A_VAR3:REAL, Examples: [8.595, 6.007, 5.934]),
(A_VAR4:REAL, Examples: [3.935, 5.938, 6.494]),
(A_VAR5:REAL, Examples: [6.362, 8.773, 9.172]),
(A_VAR6:REAL, Examples: [8.626, 3.579, 3.202]),
(A_VAR7:REAL, Examples: [4.624, 6.349, 6.157]),
(A_VAR8:REAL, Examples: [8.324, 4.694, 4.822]),
(A_VAR9:REAL, Examples: [5.233, 6.884, 7.942]),
(A_VAR10:REAL, Examples: [6.232, 7.062, 7.901]),
(A_VAR11:REAL, Examples: [5.205, 7.319, 7.928]),
(A_VAR12:REAL, Examples: [8.231, 3.72, 2.33]),
(A_VAR13:REAL, Examples: [6.746, 6.405, 6.029]),
(A_VAR14:REAL, Examples: [8.679, 7.202, 6.455]),
(A_VAR15:REAL, Examples: [5.292, 4.932, 4.72]),
(A_VAR16:REAL, Examples: [3.5, 7.969, 8.564]),
(A_VAR17:REAL, Examples: [5.512, 8.15, 8.342]),
(A_VAR18:REAL, Examples: [5.783, 5.633, 4.938])
]
# Table: Sales
[
(EVENTID:INTEGER, Primary Key, Examples: [0, 1, 2]),
(REFID:INTEGER, Examples: [0, 1, 2]),
(EVENT_DATE:DATETIME, Examples: [2006-12-21 12:00:00]),
(AMOUNT:REAL, Examples: [17.907, 17.401, 13.277])
]
【Foreign keys】
Customers.GEOID=Demog.GEOID
Mailings1_2.REFID=Customers.ID
Sales.REFID=Customers.ID

    【Question】
    What is the marital status of the customer ages 62 with an level of education of 7? customer ages 62 with an level of education of 7 refer age = 62 where EDUCATIONNUM = 7;

    【Evidence】
    customer ages 62 with an level of education of 7 refer age = 62 where EDUCATIONNUM = 7;

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT DISTINCT MARITAL_STATUS FROM Customers WHERE EDUCATIONNUM = 7 AND age = 62