1sf/bird-sql-train-with-schema huggingface dataset:
Database: public_review_platform
Tables: Attributes, Categories, Compliments, Days, Years, Business_Attributes, Business_Categories, Business_Hours, Checkins, Elite, Reviews, Tips, Users_Compliments, Business, Users
Columns (table index, column name): -1, *, 0, attribute_id, 0, attribute_name, 1, category_id, 1, category_name, 2, compliment_id, 2, compliment_type, 3, day_id, 3, day_of_week, 4, year_id, 4, actual_year, 5, attribute_id, 5, business_id, 5, attribute_value, 6, business_id, 6, category_id, 7, business_id, 7, day_id, 7, opening_time, 7, closing_time, 8, business_id, 8, day_id, 8, label_time_0, 8, label_time_1, 8, label_time_2, 8, label_time_3, 8, label_time_4, 8, label_time_5, 8, label_time_6, 8, label_time_7, 8, label_time_8, 8, label_time_9, 8, label_time_10, 8, label_time_11, 8, label_time_12, 8, label_time_13, 8, label_time_14, 8, label_time_15, 8, label_time_16, 8, label_time_17, 8, label_time_18, 8, label_time_19, 8, label_time_20, 8, label_time_21, 8, label_time_22, 8, label_time_23, 9, user_id, 9, year_id, 10, business_id, 10, user_id, 10, review_stars, 10, review_votes_funny, 10, review_votes_useful, 10, review_votes_cool, 10, review_length, 11, business_id, 11, user_id, 11, likes, 11, tip_length, 12, compliment_id, 12, user_id, 12, number_of_compliments, 13, business_id, 13, active, 13, city, 13, state, 13, stars, 13, review_count, 14, user_id, 14, user_yelping_since_year, 14, user_average_stars, 14, user_votes_funny, 14, user_votes_useful, 14, user_votes_cool, 14, user_review_count, 14, user_fans
Question: Which businesses with the category name Accessories have opening hours before 7AM?
Evidence: opening hours before 7AM refer to opening_time < '7AM'; businesses refer to business_id;
SQL: SELECT T1.business_id FROM Business_Hours AS T1 INNER JOIN Business_Categories AS T2 ON T1.business_id = T2.business_id INNER JOIN Categories AS T3 ON T2.category_id = T3.category_id WHERE T3.category_name = 'Accessories' AND SUBSTR(T1.opening_time, -4, 2) * 1 < 7 AND T1.opening_time LIKE '%AM'
Database: public_review_platform
Tables: Attributes, Categories, Compliments, Days, Years, Business_Attributes, Business_Categories, Business_Hours, Checkins, Elite, Reviews, Tips, Users_Compliments, Business, Users
Columns (table index, column name): -1, *, 0, attribute_id, 0, attribute_name, 1, category_id, 1, category_name, 2, compliment_id, 2, compliment_type, 3, day_id, 3, day_of_week, 4, year_id, 4, actual_year, 5, attribute_id, 5, business_id, 5, attribute_value, 6, business_id, 6, category_id, 7, business_id, 7, day_id, 7, opening_time, 7, closing_time, 8, business_id, 8, day_id, 8, label_time_0, 8, label_time_1, 8, label_time_2, 8, label_time_3, 8, label_time_4, 8, label_time_5, 8, label_time_6, 8, label_time_7, 8, label_time_8, 8, label_time_9, 8, label_time_10, 8, label_time_11, 8, label_time_12, 8, label_time_13, 8, label_time_14, 8, label_time_15, 8, label_time_16, 8, label_time_17, 8, label_time_18, 8, label_time_19, 8, label_time_20, 8, label_time_21, 8, label_time_22, 8, label_time_23, 9, user_id, 9, year_id, 10, business_id, 10, user_id, 10, review_stars, 10, review_votes_funny, 10, review_votes_useful, 10, review_votes_cool, 10, review_length, 11, business_id, 11, user_id, 11, likes, 11, tip_length, 12, compliment_id, 12, user_id, 12, number_of_compliments, 13, business_id, 13, active, 13, city, 13, state, 13, stars, 13, review_count, 14, user_id, 14, user_yelping_since_year, 14, user_average_stars, 14, user_votes_funny, 14, user_votes_useful, 14, user_votes_cool, 14, user_review_count, 14, user_fans
Question: Among the active businesses in Arizona, how many businesses work after 12PM?
Evidence: active businesses in Arizona refer to business_id where state = 'Arizona' and active = 'true'; work after 12PM refer to opening_time > '12PM';
SQL: SELECT COUNT(DISTINCT T2.business_id) FROM Business_Hours AS T1 INNER JOIN Business AS T2 ON T1.business_id = T2.business_id INNER JOIN Business_Categories AS T3 ON T2.business_id = T3.business_id INNER JOIN Categories AS T4 ON T3.category_id = T4.category_id WHERE T2.active = 'true' AND T2.state = 'AZ' AND T1.opening_time > '12PM'
Database: public_review_platform
Tables: Attributes, Categories, Compliments, Days, Years, Business_Attributes, Business_Categories, Business_Hours, Checkins, Elite, Reviews, Tips, Users_Compliments, Business, Users
Columns (table index, column name): -1, *, 0, attribute_id, 0, attribute_name, 1, category_id, 1, category_name, 2, compliment_id, 2, compliment_type, 3, day_id, 3, day_of_week, 4, year_id, 4, actual_year, 5, attribute_id, 5, business_id, 5, attribute_value, 6, business_id, 6, category_id, 7, business_id, 7, day_id, 7, opening_time, 7, closing_time, 8, business_id, 8, day_id, 8, label_time_0, 8, label_time_1, 8, label_time_2, 8, label_time_3, 8, label_time_4, 8, label_time_5, 8, label_time_6, 8, label_time_7, 8, label_time_8, 8, label_time_9, 8, label_time_10, 8, label_time_11, 8, label_time_12, 8, label_time_13, 8, label_time_14, 8, label_time_15, 8, label_time_16, 8, label_time_17, 8, label_time_18, 8, label_time_19, 8, label_time_20, 8, label_time_21, 8, label_time_22, 8, label_time_23, 9, user_id, 9, year_id, 10, business_id, 10, user_id, 10, review_stars, 10, review_votes_funny, 10, review_votes_useful, 10, review_votes_cool, 10, review_length, 11, business_id, 11, user_id, 11, likes, 11, tip_length, 12, compliment_id, 12, user_id, 12, number_of_compliments, 13, business_id, 13, active, 13, city, 13, state, 13, stars, 13, review_count, 14, user_id, 14, user_yelping_since_year, 14, user_average_stars, 14, user_votes_funny, 14, user_votes_useful, 14, user_votes_cool, 14, user_review_count, 14, user_fans
Question: Please provide the name of businesses with user id "16328".
Evidence: name of business refers to category_name;
SQL: SELECT T1.category_name FROM Categories AS T1 INNER JOIN Business_Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Tips AS T3 ON T2.business_id = T3.business_id WHERE T3.user_id = 16328
Database: public_review_platform
Tables: Attributes, Categories, Compliments, Days, Years, Business_Attributes, Business_Categories, Business_Hours, Checkins, Elite, Reviews, Tips, Users_Compliments, Business, Users
Columns (table index, column name): -1, *, 0, attribute_id, 0, attribute_name, 1, category_id, 1, category_name, 2, compliment_id, 2, compliment_type, 3, day_id, 3, day_of_week, 4, year_id, 4, actual_year, 5, attribute_id, 5, business_id, 5, attribute_value, 6, business_id, 6, category_id, 7, business_id, 7, day_id, 7, opening_time, 7, closing_time, 8, business_id, 8, day_id, 8, label_time_0, 8, label_time_1, 8, label_time_2, 8, label_time_3, 8, label_time_4, 8, label_time_5, 8, label_time_6, 8, label_time_7, 8, label_time_8, 8, label_time_9, 8, label_time_10, 8, label_time_11, 8, label_time_12, 8, label_time_13, 8, label_time_14, 8, label_time_15, 8, label_time_16, 8, label_time_17, 8, label_time_18, 8, label_time_19, 8, label_time_20, 8, label_time_21, 8, label_time_22, 8, label_time_23, 9, user_id, 9, year_id, 10, business_id, 10, user_id, 10, review_stars, 10, review_votes_funny, 10, review_votes_useful, 10, review_votes_cool, 10, review_length, 11, business_id, 11, user_id, 11, likes, 11, tip_length, 12, compliment_id, 12, user_id, 12, number_of_compliments, 13, business_id, 13, active, 13, city, 13, state, 13, stars, 13, review_count, 14, user_id, 14, user_yelping_since_year, 14, user_average_stars, 14, user_votes_funny, 14, user_votes_useful, 14, user_votes_cool, 14, user_review_count, 14, user_fans
Question: How many businesses have the category named food? List those businesses and find the percentage of businesses with less than 2 stars.
Evidence: businesses have the category named food refer to business_id where category_name = 'Food'; DIVIDE(COUNT(business_id where category_name = 'Food' and stars < 2), COUNT(business_id where category_name = 'Food')) as percentage;
SQL: SELECT T3.business_id, CAST((( SELECT COUNT(business_id) FROM Business WHERE stars < 2 ) - ( SELECT COUNT(business_id) FROM Business WHERE stars > 2 )) AS REAL) * 100 / ( SELECT COUNT(stars) FROM Business ) FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Business AS T3 ON T1.business_id = T3.business_id WHERE T2.category_name = 'Food'
Database: public_review_platform
Tables: Attributes, Categories, Compliments, Days, Years, Business_Attributes, Business_Categories, Business_Hours, Checkins, Elite, Reviews, Tips, Users_Compliments, Business, Users
Columns (table index, column name): -1, *, 0, attribute_id, 0, attribute_name, 1, category_id, 1, category_name, 2, compliment_id, 2, compliment_type, 3, day_id, 3, day_of_week, 4, year_id, 4, actual_year, 5, attribute_id, 5, business_id, 5, attribute_value, 6, business_id, 6, category_id, 7, business_id, 7, day_id, 7, opening_time, 7, closing_time, 8, business_id, 8, day_id, 8, label_time_0, 8, label_time_1, 8, label_time_2, 8, label_time_3, 8, label_time_4, 8, label_time_5, 8, label_time_6, 8, label_time_7, 8, label_time_8, 8, label_time_9, 8, label_time_10, 8, label_time_11, 8, label_time_12, 8, label_time_13, 8, label_time_14, 8, label_time_15, 8, label_time_16, 8, label_time_17, 8, label_time_18, 8, label_time_19, 8, label_time_20, 8, label_time_21, 8, label_time_22, 8, label_time_23, 9, user_id, 9, year_id, 10, business_id, 10, user_id, 10, review_stars, 10, review_votes_funny, 10, review_votes_useful, 10, review_votes_cool, 10, review_length, 11, business_id, 11, user_id, 11, likes, 11, tip_length, 12, compliment_id, 12, user_id, 12, number_of_compliments, 13, business_id, 13, active, 13, city, 13, state, 13, stars, 13, review_count, 14, user_id, 14, user_yelping_since_year, 14, user_average_stars, 14, user_votes_funny, 14, user_votes_useful, 14, user_votes_cool, 14, user_review_count, 14, user_fans
Question: Calculate the percentage of businesses with the category name food that are open from 7AM to 8PM in the businesses with the same time.
Evidence: DIVIDE(COUNT(business_id where category_name = 'Food' and opening_time = '7AM' and closing_time = '8PM'), COUNT(business_id where opening_time = '7AM' and closing_time = '8PM')) as percentage;
SQL: SELECT CAST(SUM(CASE WHEN T3.category_name = 'Food' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T3.category_name) FROM Business_Categories AS T1 INNER JOIN Business AS T2 ON T1.business_id = T2.business_id INNER JOIN Categories AS T3 ON T1.category_id = T3.category_id
Database: public_review_platform
Tables: Attributes, Categories, Compliments, Days, Years, Business_Attributes, Business_Categories, Business_Hours, Checkins, Elite, Reviews, Tips, Users_Compliments, Business, Users
Columns (table index, column name): -1, *, 0, attribute_id, 0, attribute_name, 1, category_id, 1, category_name, 2, compliment_id, 2, compliment_type, 3, day_id, 3, day_of_week, 4, year_id, 4, actual_year, 5, attribute_id, 5, business_id, 5, attribute_value, 6, business_id, 6, category_id, 7, business_id, 7, day_id, 7, opening_time, 7, closing_time, 8, business_id, 8, day_id, 8, label_time_0, 8, label_time_1, 8, label_time_2, 8, label_time_3, 8, label_time_4, 8, label_time_5, 8, label_time_6, 8, label_time_7, 8, label_time_8, 8, label_time_9, 8, label_time_10, 8, label_time_11, 8, label_time_12, 8, label_time_13, 8, label_time_14, 8, label_time_15, 8, label_time_16, 8, label_time_17, 8, label_time_18, 8, label_time_19, 8, label_time_20, 8, label_time_21, 8, label_time_22, 8, label_time_23, 9, user_id, 9, year_id, 10, business_id, 10, user_id, 10, review_stars, 10, review_votes_funny, 10, review_votes_useful, 10, review_votes_cool, 10, review_length, 11, business_id, 11, user_id, 11, likes, 11, tip_length, 12, compliment_id, 12, user_id, 12, number_of_compliments, 13, business_id, 13, active, 13, city, 13, state, 13, stars, 13, review_count, 14, user_id, 14, user_yelping_since_year, 14, user_average_stars, 14, user_votes_funny, 14, user_votes_useful, 14, user_votes_cool, 14, user_review_count, 14, user_fans
Question: Write down the number of running business with each review count in Cave Creek city.
Evidence: number of running business refers to COUNT(business_id) where active = 'true'; each review count includes review_count = 'High', review_count = 'Medium', review_count = 'Low';
SQL: SELECT SUM(CASE WHEN review_count = 'High' THEN 1 ELSE 0 END) AS high , SUM(CASE WHEN review_count = 'Medium' THEN 1 ELSE 0 END) AS Medium , SUM(CASE WHEN review_count = 'Low' THEN 1 ELSE 0 END) AS low FROM Business WHERE city = 'Cave Creek' AND active = 'true'
Database: public_review_platform
Tables: Attributes, Categories, Compliments, Days, Years, Business_Attributes, Business_Categories, Business_Hours, Checkins, Elite, Reviews, Tips, Users_Compliments, Business, Users
Columns (table index, column name): -1, *, 0, attribute_id, 0, attribute_name, 1, category_id, 1, category_name, 2, compliment_id, 2, compliment_type, 3, day_id, 3, day_of_week, 4, year_id, 4, actual_year, 5, attribute_id, 5, business_id, 5, attribute_value, 6, business_id, 6, category_id, 7, business_id, 7, day_id, 7, opening_time, 7, closing_time, 8, business_id, 8, day_id, 8, label_time_0, 8, label_time_1, 8, label_time_2, 8, label_time_3, 8, label_time_4, 8, label_time_5, 8, label_time_6, 8, label_time_7, 8, label_time_8, 8, label_time_9, 8, label_time_10, 8, label_time_11, 8, label_time_12, 8, label_time_13, 8, label_time_14, 8, label_time_15, 8, label_time_16, 8, label_time_17, 8, label_time_18, 8, label_time_19, 8, label_time_20, 8, label_time_21, 8, label_time_22, 8, label_time_23, 9, user_id, 9, year_id, 10, business_id, 10, user_id, 10, review_stars, 10, review_votes_funny, 10, review_votes_useful, 10, review_votes_cool, 10, review_length, 11, business_id, 11, user_id, 11, likes, 11, tip_length, 12, compliment_id, 12, user_id, 12, number_of_compliments, 13, business_id, 13, active, 13, city, 13, state, 13, stars, 13, review_count, 14, user_id, 14, user_yelping_since_year, 14, user_average_stars, 14, user_votes_funny, 14, user_votes_useful, 14, user_votes_cool, 14, user_review_count, 14, user_fans
Question: Calculate the yearly average user who started using Yelp from the year of 2005 to 2014.
Evidence: avg(user_id) where user_yelping_since_year BETWEEN '2005' AND '2014';
SQL: SELECT AVG(user_id) FROM Users WHERE user_yelping_since_year >= 2005 AND user_yelping_since_year <= 2015
Database: public_review_platform
Tables: Attributes, Categories, Compliments, Days, Years, Business_Attributes, Business_Categories, Business_Hours, Checkins, Elite, Reviews, Tips, Users_Compliments, Business, Users
Columns (table index, column name): -1, *, 0, attribute_id, 0, attribute_name, 1, category_id, 1, category_name, 2, compliment_id, 2, compliment_type, 3, day_id, 3, day_of_week, 4, year_id, 4, actual_year, 5, attribute_id, 5, business_id, 5, attribute_value, 6, business_id, 6, category_id, 7, business_id, 7, day_id, 7, opening_time, 7, closing_time, 8, business_id, 8, day_id, 8, label_time_0, 8, label_time_1, 8, label_time_2, 8, label_time_3, 8, label_time_4, 8, label_time_5, 8, label_time_6, 8, label_time_7, 8, label_time_8, 8, label_time_9, 8, label_time_10, 8, label_time_11, 8, label_time_12, 8, label_time_13, 8, label_time_14, 8, label_time_15, 8, label_time_16, 8, label_time_17, 8, label_time_18, 8, label_time_19, 8, label_time_20, 8, label_time_21, 8, label_time_22, 8, label_time_23, 9, user_id, 9, year_id, 10, business_id, 10, user_id, 10, review_stars, 10, review_votes_funny, 10, review_votes_useful, 10, review_votes_cool, 10, review_length, 11, business_id, 11, user_id, 11, likes, 11, tip_length, 12, compliment_id, 12, user_id, 12, number_of_compliments, 13, business_id, 13, active, 13, city, 13, state, 13, stars, 13, review_count, 14, user_id, 14, user_yelping_since_year, 14, user_average_stars, 14, user_votes_funny, 14, user_votes_useful, 14, user_votes_cool, 14, user_review_count, 14, user_fans
Question: What is the active and inactive ratio of the business with the review count of low.
Evidence: DIVIDE(COUNT(business_id where review_count = 'Low' and active = 'true'), COUNT(business_id where review_count = 'Low' and active = 'false'));
SQL: SELECT CAST(SUM(CASE WHEN active = 'true' THEN 1 ELSE 0 END) AS REAL) / SUM(CASE WHEN active = 'false' THEN 1 ELSE 0 END) AS radio FROM Business WHERE review_count = 'Low'
Database: public_review_platform
Tables: Attributes, Categories, Compliments, Days, Years, Business_Attributes, Business_Categories, Business_Hours, Checkins, Elite, Reviews, Tips, Users_Compliments, Business, Users
Columns (table index, column name): -1, *, 0, attribute_id, 0, attribute_name, 1, category_id, 1, category_name, 2, compliment_id, 2, compliment_type, 3, day_id, 3, day_of_week, 4, year_id, 4, actual_year, 5, attribute_id, 5, business_id, 5, attribute_value, 6, business_id, 6, category_id, 7, business_id, 7, day_id, 7, opening_time, 7, closing_time, 8, business_id, 8, day_id, 8, label_time_0, 8, label_time_1, 8, label_time_2, 8, label_time_3, 8, label_time_4, 8, label_time_5, 8, label_time_6, 8, label_time_7, 8, label_time_8, 8, label_time_9, 8, label_time_10, 8, label_time_11, 8, label_time_12, 8, label_time_13, 8, label_time_14, 8, label_time_15, 8, label_time_16, 8, label_time_17, 8, label_time_18, 8, label_time_19, 8, label_time_20, 8, label_time_21, 8, label_time_22, 8, label_time_23, 9, user_id, 9, year_id, 10, business_id, 10, user_id, 10, review_stars, 10, review_votes_funny, 10, review_votes_useful, 10, review_votes_cool, 10, review_length, 11, business_id, 11, user_id, 11, likes, 11, tip_length, 12, compliment_id, 12, user_id, 12, number_of_compliments, 13, business_id, 13, active, 13, city, 13, state, 13, stars, 13, review_count, 14, user_id, 14, user_yelping_since_year, 14, user_average_stars, 14, user_votes_funny, 14, user_votes_useful, 14, user_votes_cool, 14, user_review_count, 14, user_fans
Question: List any five of user ID who became elite user in 2006.
Evidence: year_id = '2006';
SQL: SELECT user_id FROM Elite WHERE year_id = 2006 LIMIT 5
Database: public_review_platform
Tables: Attributes, Categories, Compliments, Days, Years, Business_Attributes, Business_Categories, Business_Hours, Checkins, Elite, Reviews, Tips, Users_Compliments, Business, Users
Columns (table index, column name): -1, *, 0, attribute_id, 0, attribute_name, 1, category_id, 1, category_name, 2, compliment_id, 2, compliment_type, 3, day_id, 3, day_of_week, 4, year_id, 4, actual_year, 5, attribute_id, 5, business_id, 5, attribute_value, 6, business_id, 6, category_id, 7, business_id, 7, day_id, 7, opening_time, 7, closing_time, 8, business_id, 8, day_id, 8, label_time_0, 8, label_time_1, 8, label_time_2, 8, label_time_3, 8, label_time_4, 8, label_time_5, 8, label_time_6, 8, label_time_7, 8, label_time_8, 8, label_time_9, 8, label_time_10, 8, label_time_11, 8, label_time_12, 8, label_time_13, 8, label_time_14, 8, label_time_15, 8, label_time_16, 8, label_time_17, 8, label_time_18, 8, label_time_19, 8, label_time_20, 8, label_time_21, 8, label_time_22, 8, label_time_23, 9, user_id, 9, year_id, 10, business_id, 10, user_id, 10, review_stars, 10, review_votes_funny, 10, review_votes_useful, 10, review_votes_cool, 10, review_length, 11, business_id, 11, user_id, 11, likes, 11, tip_length, 12, compliment_id, 12, user_id, 12, number_of_compliments, 13, business_id, 13, active, 13, city, 13, state, 13, stars, 13, review_count, 14, user_id, 14, user_yelping_since_year, 14, user_average_stars, 14, user_votes_funny, 14, user_votes_useful, 14, user_votes_cool, 14, user_review_count, 14, user_fans
Question: Write down the any five of ID and name of category that starts with alphabet "P".
Evidence: category that starts with alphabet "P" refers to category_name like 'P%';
SQL: SELECT category_id, category_name FROM Categories WHERE category_name LIKE 'P%' LIMIT 5
Database: public_review_platform
Tables: Attributes, Categories, Compliments, Days, Years, Business_Attributes, Business_Categories, Business_Hours, Checkins, Elite, Reviews, Tips, Users_Compliments, Business, Users
Columns (table index, column name): -1, *, 0, attribute_id, 0, attribute_name, 1, category_id, 1, category_name, 2, compliment_id, 2, compliment_type, 3, day_id, 3, day_of_week, 4, year_id, 4, actual_year, 5, attribute_id, 5, business_id, 5, attribute_value, 6, business_id, 6, category_id, 7, business_id, 7, day_id, 7, opening_time, 7, closing_time, 8, business_id, 8, day_id, 8, label_time_0, 8, label_time_1, 8, label_time_2, 8, label_time_3, 8, label_time_4, 8, label_time_5, 8, label_time_6, 8, label_time_7, 8, label_time_8, 8, label_time_9, 8, label_time_10, 8, label_time_11, 8, label_time_12, 8, label_time_13, 8, label_time_14, 8, label_time_15, 8, label_time_16, 8, label_time_17, 8, label_time_18, 8, label_time_19, 8, label_time_20, 8, label_time_21, 8, label_time_22, 8, label_time_23, 9, user_id, 9, year_id, 10, business_id, 10, user_id, 10, review_stars, 10, review_votes_funny, 10, review_votes_useful, 10, review_votes_cool, 10, review_length, 11, business_id, 11, user_id, 11, likes, 11, tip_length, 12, compliment_id, 12, user_id, 12, number_of_compliments, 13, business_id, 13, active, 13, city, 13, state, 13, stars, 13, review_count, 14, user_id, 14, user_yelping_since_year, 14, user_average_stars, 14, user_votes_funny, 14, user_votes_useful, 14, user_votes_cool, 14, user_review_count, 14, user_fans
Question: Provide the list of user ID along with review star of which has the review length of medium with business ID of 35.
Evidence: ;
SQL: SELECT user_id, review_stars FROM Reviews WHERE business_id = 15 AND review_length = 'Medium'
Database: public_review_platform
Tables: Attributes, Categories, Compliments, Days, Years, Business_Attributes, Business_Categories, Business_Hours, Checkins, Elite, Reviews, Tips, Users_Compliments, Business, Users
Columns (table index, column name): -1, *, 0, attribute_id, 0, attribute_name, 1, category_id, 1, category_name, 2, compliment_id, 2, compliment_type, 3, day_id, 3, day_of_week, 4, year_id, 4, actual_year, 5, attribute_id, 5, business_id, 5, attribute_value, 6, business_id, 6, category_id, 7, business_id, 7, day_id, 7, opening_time, 7, closing_time, 8, business_id, 8, day_id, 8, label_time_0, 8, label_time_1, 8, label_time_2, 8, label_time_3, 8, label_time_4, 8, label_time_5, 8, label_time_6, 8, label_time_7, 8, label_time_8, 8, label_time_9, 8, label_time_10, 8, label_time_11, 8, label_time_12, 8, label_time_13, 8, label_time_14, 8, label_time_15, 8, label_time_16, 8, label_time_17, 8, label_time_18, 8, label_time_19, 8, label_time_20, 8, label_time_21, 8, label_time_22, 8, label_time_23, 9, user_id, 9, year_id, 10, business_id, 10, user_id, 10, review_stars, 10, review_votes_funny, 10, review_votes_useful, 10, review_votes_cool, 10, review_length, 11, business_id, 11, user_id, 11, likes, 11, tip_length, 12, compliment_id, 12, user_id, 12, number_of_compliments, 13, business_id, 13, active, 13, city, 13, state, 13, stars, 13, review_count, 14, user_id, 14, user_yelping_since_year, 14, user_average_stars, 14, user_votes_funny, 14, user_votes_useful, 14, user_votes_cool, 14, user_review_count, 14, user_fans
Question: List down the business ID and attribute value of the attribute name of "payment_types_visa".
SQL: SELECT T2.business_id, T2.attribute_value FROM Attributes AS T1 INNER JOIN Business_Attributes AS T2 ON T1.attribute_id = T2.attribute_id WHERE T1.attribute_name = 'payment_types_visa'