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: In which year did the user who gave the most number of "5" star reviews join the Yelp?
Evidence: year the user join the Yelp refers to user_yelping_since_year; star reviews refers to review_stars;
SQL: SELECT T2.user_yelping_since_year FROM Reviews AS T1 INNER JOIN Users AS T2 ON T1.user_id = T2.user_id WHERE T1.review_stars = 5 GROUP BY T2.user_yelping_since_year ORDER BY COUNT(T1.review_stars) DESC LIMIT 1
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: For the user who gave the most number of long reviews, what is his/her averge ratings of all review?
Evidence: long reviews refers to review_length = 'long'; most number of long reviews refers to MAX(COUNT(review_length = 'long')); average ratings = AVG(review_stars);
SQL: SELECT CAST(SUM(T1.review_stars) AS REAL) / COUNT(T1.review_stars) FROM Reviews AS T1 INNER JOIN Users AS T2 ON T1.user_id = T2.user_id WHERE T1.review_length LIKE 'Long' GROUP BY T1.user_id ORDER BY COUNT(T1.review_length) DESC LIMIT 1
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: For the Yelp business which had the most number of "long" reviews, which category does it belong to?
Evidence: long reviews refers to review_length = 'long'; most number of long reviews refers to MAX(COUNT(review_length = 'long')); category refers to category_name;
SQL: SELECT T4.category_name FROM Reviews 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 T1.review_length LIKE 'Long' GROUP BY T2.business_id ORDER BY COUNT(T1.review_length) DESC LIMIT 1
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: For the Yelp business which had the most number of "short" tips, which category does it belong to?
Evidence: short tips refers to tip_length = 'short'; most number of short tips refers to MAX(COUNT(tip_length = 'short')); category refers to category_name;
SQL: SELECT DISTINCT T1.category_name FROM Categories AS T1 INNER JOIN Business_Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Business AS T3 ON T2.business_id = T3.business_id INNER JOIN Tips AS T4 ON T3.business_id = T4.business_id WHERE T4.tip_length LIKE 'short'
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: In which year did the user who has given the most number of "short" tips join the Yelp?
Evidence: year the user join the Yelp refers to user_yelping_since_year; most number of short tips refers to MAX(COUNT(tip_length = 'Short'));
SQL: SELECT T2.user_yelping_since_year FROM Tips AS T1 INNER JOIN Users AS T2 ON T1.user_id = T2.user_id WHERE T1.tip_length LIKE 'short' GROUP BY T2.user_yelping_since_year ORDER BY COUNT(T1.tip_length) DESC LIMIT 1
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: User No. 70271 only has given one tip to the Yelp business, which category was that business belonged to?
Evidence: user No. refers to user_id; short tip refers to tip_length = 'short'; category refers to category_name;
SQL: SELECT T4.category_name FROM Tips 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 T1.user_id = 70271
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: There was only one tip that user No. 69722 gave to the Yelp business, what was the ratings of that business?
Evidence: short tip refers to tip_lenghth = 'short'; user No. refers to user_id; ratings refers to stars; stars = 5 means great experience; stars = 4 means good experience; stars = 3 means average experience; stars = 2 means bad experience; stars = 1 means terrible experience;

SQL: SELECT T2.stars FROM Tips AS T1 INNER JOIN Business AS T2 ON T1.business_id = T2.business_id WHERE T1.user_id = 69722
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: Give the percentage of "Automotive" businesses among all the Yelp businesses.
Evidence: automotive businesses refers to category_name = 'Automotive'; percentage = MULTIPLY(DIVIDE(SUM(category_name = 'Automotive'), COUNT(business_id)), 1.0);
SQL: SELECT CAST(SUM(CASE WHEN T2.category_name LIKE 'Automotive' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.business_id) AS "percentage" FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.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: What percentage more for the "Women's Clothing" Yelp businesses to "Men's Clothing"?
Evidence: Women's clothing refers to category_name = 'Women''s Clothing'; Men's clothing refers to category_name = 'Men''s Clothing'; percentage more = MULTIPLY(DIVIDE(SUBTRACT(SUM(category_name = 'Women''s Clothing'), SUM(category_name = 'Men''s Clothing')), COUNT(business_id)), 1.0);
SQL: SELECT CAST(SUM(CASE WHEN T2.category_name LIKE 'Women''s Clothing' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.business_id) - CAST(SUM(CASE WHEN T2.category_name LIKE 'Men''s Clothing' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.business_id) AS "more percentage" FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.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: Give the number of users who joined Yelp since "2004".
Evidence: joined yelp since 2004 refers to user_yelping_since_year = 2004;
SQL: SELECT COUNT(user_id) FROM Users WHERE user_yelping_since_year = 2004
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 users who have joined Yelp since "2005" but have no fans?
Evidence: joined Yelp since 2005 refers to user_yelping_since_year = 2005; no fans refers to user_fans = 'None';
SQL: SELECT COUNT(user_id) FROM Users WHERE user_yelping_since_year = 2005 AND user_fans LIKE 'None'
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: State the number of actively running Yelp businesses in "Tolleson".
Evidence: actively running refers to active = 'TRUE'; Tolleson refers to city = 'Tolleson';
SQL: SELECT COUNT(business_id) FROM Business WHERE city LIKE 'Tolleson' AND active LIKE 'TRUE'