db_id stringclasses 68 values | question stringlengths 24 325 | evidence stringlengths 0 580 | SQL stringlengths 23 728 |
|---|---|---|---|
public_review_platform | Does Yelp business No."11825" have a "parking lot"? | business No."11825" refers to business_id = '12476'; have a "parking lot" refers to attribute_value = 'parking_lot' | SELECT T1.attribute_value FROM Business_Attributes AS T1 INNER JOIN Attributes AS T2 ON T1.attribute_id = T2.attribute_id WHERE T1.business_id = 11825 AND T2.attribute_name = 'parking_lot' |
public_review_platform | Is the payment in mastercard possible for the Yelp business No."12476"? | Yelp business No."12476" refers to business_id = '12476'; payment in mastercard refers to attribute_value = 'payment_types_mastercard' | SELECT T1.attribute_value FROM Business_Attributes AS T1 INNER JOIN Attributes AS T2 ON T1.attribute_id = T2.attribute_id WHERE T1.business_id = 12476 AND T2.attribute_name = 'payment_types_mastercard' |
public_review_platform | What is the percentage for the Yelp businesses in "Pets" category of all businesses? | businesses in "Pets" category refers to category_name = 'Pets'; percentage refers to DIVIDE(COUNT(category_name = 'Pets'), COUNT(business_id)) * 100% | SELECT CAST(SUM(CASE WHEN T2.category_name = 'Pets' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T2.category_name) FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.category_id |
public_review_platform | How many times is the number of "Women's Clothing" Yelp businesses to "Men's Clothing"? | "Women's Clothing" Yelp businesses refers to category_name = 'Women''s Clothing'; "Men's Clothing" refers to category_name = 'Men''s Clothing'; times refers to DIVIDE(COUNT(category_name = 'Women''s Clothing'), COUNT(category_name = 'Men''s Clothing')) | SELECT CAST(SUM(CASE WHEN T2.category_name = 'Women''s Clothing' THEN 1 ELSE 0 END) AS REAL) / SUM(CASE WHEN T2.category_name = 'Men''s Clothing' THEN 1 ELSE 0 END) AS TIMES FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.category_id |
public_review_platform | Write down the ID, active status and city of the business which are in CA state. | the ID refers to business_id; active status refers to active; active = 'true' means the business is still running; active = 'false' means the business is closed or not running now | SELECT business_id, active, city FROM Business WHERE state = 'CA' AND active = 'true' |
public_review_platform | Calculate the percentage of running business among all business. | running business refers to active = 'true'; percentage refers to DIVIDE(COUNT(active = 'true'), COUNT(business_id)) * 100% | SELECT CAST(SUM(CASE WHEN active = 'true' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(business_id) FROM Business |
public_review_platform | Among all attribute names, list down the ID and attribute name which start with "music". | attribute name which start with "music" refers to attribute_name LIKE 'music%' | SELECT attribute_id, attribute_name FROM Attributes WHERE attribute_name LIKE 'music%' |
public_review_platform | Between 2006 and 2007, which year ID had the greater number in elite user? | 2006 and 2007 refers to BETWEEN 2006 AND 2007; greater number in elite user refers to count(user_id) | SELECT year_id FROM Elite WHERE year_id IN (2006, 2007) GROUP BY year_id ORDER BY COUNT(user_id) DESC LIMIT 1 |
public_review_platform | Based on all user compliments, find the percentage of low number of compliments on all compliments ID. | low number of compliments refers to number_of_compliments = 'Low'; percentage refers to DIVIDE(COUNT(number_of_compliments = 'Low'), COUNT(user_id)) * 100 | SELECT CAST(SUM(CASE WHEN number_of_compliments = 'Low' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(user_id) FROM Users_compliments |
public_review_platform | List down the business ID and user ID who got uber for cool votes. | got uber for cool votes refers to review_votes_cool = 'Uber' | SELECT business_id, user_id FROM Reviews WHERE review_votes_cool = 'Uber' |
public_review_platform | Write the user ID, business ID and tips length of who started using Yelp since 2004 and had high followers. | started using Yelp since 2004 refers to user_yelping_since_year = '2004'; had high followers refers to user_fans = 'High' | SELECT T1.user_id, T2.business_id, T2.tip_length FROM Users AS T1 INNER JOIN Tips AS T2 ON T1.user_id = T2.user_id WHERE T1.user_yelping_since_year = 2004 AND T1.user_fans = 'High' |
public_review_platform | Among the review votes of funny and cool hit uber with long review length, describe the business ID, active status, user ID and user year of joining Yelp. | review votes of funny refers to review_votes_funny = 'Uber'; cool hit uber refers to review_votes_cool = 'Uber'; user year of joining Yelp refers to user_yelping_since_year | SELECT T1.business_id, T1.active, T3.user_id, T3.user_yelping_since_year FROM Business AS T1 INNER JOIN Reviews AS T2 ON T1.business_id = T2.business_id INNER JOIN Users AS T3 ON T2.user_id = T3.user_id WHERE T2.review_votes_cool = 'Uber' AND T2.review_votes_funny = 'Uber' AND T2.review_length = 'Long' |
public_review_platform | Under the attribute name of "music_playlist", describe the attribute ID, business ID, city and inactive status. | active status refers to active; active = 'true' means the business is still running; active = 'false' means the business is inactive or not running now | SELECT T1.attribute_id, T2.business_id, T3.city FROM Attributes AS T1 INNER JOIN Business_Attributes AS T2 ON T1.attribute_id = T2.attribute_id INNER JOIN Business AS T3 ON T2.business_id = T3.business_id WHERE T1.attribute_name = 'music_playlist' AND T3.active = 'false' |
public_review_platform | Calculate the percentage of business with attribute name of "Accepts Credit Cards". | percentage refers to DIVIDE(COUNT(attribute_name = 'Accepts Credit Cards'), COUNT(business_id))*100% | SELECT CAST(SUM(CASE WHEN T1.attribute_name = 'Accepts Credit Cards' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.attribute_name) FROM Attributes AS T1 INNER JOIN Business_Attributes AS T2 ON T1.attribute_id = T2.attribute_id |
public_review_platform | Among the stopped businesses in San Tan Valley city, list down the user ID and review length of who had great experience. | stop businesses refers to active = 'false'; great experience refers to review_stars = 5
| SELECT T2.user_id, T2.review_length FROM Business AS T1 INNER JOIN Reviews AS T2 ON T1.business_id = T2.business_id WHERE T1.city = 'San Tan Valley' AND T1.active = 'false' AND T2.review_stars = 5 |
public_review_platform | Mention the user average star, elite year and the compliment type of user ID 6027 whereby number of compliments reach uber. | number of compliments reach uber refers to number_of_compliments = 'Uber'; elite year refers to year_id; user average star refers to user_average_stars | SELECT T2.user_average_stars, T1.year_id, T4.compliment_type, T3.number_of_compliments FROM Elite AS T1 INNER JOIN Users AS T2 ON T1.user_id = T2.user_id INNER JOIN Users_Compliments AS T3 ON T2.user_id = T3.user_id INNER JOIN Compliments AS T4 ON T3.compliment_id = T4.compliment_id INNER JOIN Years AS T5 ON T1.year_id = T5.year_id WHERE T3.number_of_compliments = 'Uber' AND T3.user_id = 6027 |
public_review_platform | Under the category name of "Coffee & Tea", mention any 5 business ID , their state and city. | SELECT T2.business_id, T3.state, T3.city 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 WHERE T1.category_name = 'Coffee & Tea' LIMIT 5 | |
public_review_platform | For the business with great experience existed in Sun Lakes city, provide the user ID who gave review on it and user followers. | with great experience refers to stars = 5 | SELECT T3.user_id, T3.user_fans FROM Business AS T1 INNER JOIN Reviews AS T2 ON T1.business_id = T2.business_id INNER JOIN Users AS T3 ON T2.user_id = T3.user_id WHERE T1.city = 'Sun Lakes' AND T1.stars = 5 |
public_review_platform | Compare the number of business between the category of "Men's Clothing" and "Women's Clothing". | category of "Men's Clothing" refers to category_name = 'Men''s Clothing'; "Women's Clothing" refers to category_name = 'Women''s Clothing' | SELECT SUM(CASE WHEN T1.category_name = 'Men''s Clothing' THEN 1 ELSE 0 END) - SUM(CASE WHEN T1.category_name = 'Women''s Clothing' THEN 1 ELSE 0 END) AS diff FROM Categories AS T1 INNER JOIN Business_Categories AS T2 ON T1.category_id = T2.category_id |
public_review_platform | Among highest quality user of under ID 100, mention compliment type which got highest compliment number and user's followers. | highest quality user refers to number_of_compliments = 'Uber'; user of under ID 100 refers to user_id < 100 ; | SELECT T1.compliment_type, T3.user_fans FROM Compliments AS T1 INNER JOIN Users_Compliments AS T2 ON T1.compliment_id = T2.compliment_id INNER JOIN Users AS T3 ON T2.user_id = T3.user_id WHERE T2.number_of_compliments = 'Uber' AND T2.user_id < 100 |
public_review_platform | List all the businesses that closed at 8PM. | closed at 8PM refers to closing_time = '8PM'; | SELECT DISTINCT business_id FROM Business_Hours WHERE closing_time = '8PM' |
public_review_platform | How many 2 stars rated business located in Phoenix, Arizona? | located in Phoenix refers to city = 'Phoenix'; Arizona refers to state = 'AZ' | SELECT COUNT(business_id) FROM Business WHERE city = 'Phoenix' AND state = 'AZ' AND stars = 2 |
public_review_platform | How many businesses in Tempe are rated as 'Wonderful experience? | in Tempe refers to city = 'Tempe'; rated as 'Wonderful experience refers to stars > 3 | SELECT COUNT(business_id) FROM Business WHERE city = 'Phoenix' AND stars > 3 |
public_review_platform | Find the percentage of 5 stars rated business. | percentage refers to DIVIDE(COUNT(stars = 5), COUNT(business_id)) * 100% | SELECT CAST(SUM(CASE WHEN stars = 5 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(stars) FROM Business |
public_review_platform | Calculate difference between business that have the highest number of reviews and business that have the lowest number of reviews. | highest number of reviews refers to SUBTRACT(MAX(COUNT(business_id), MIN(COUNT(business_id)))) | SELECT ( SELECT COUNT(business_id) FROM Reviews GROUP BY business_id ORDER BY COUNT(business_id) DESC LIMIT 1 ) - ( SELECT COUNT(business_id) FROM Reviews GROUP BY business_id ORDER BY COUNT(business_id) ASC LIMIT 1 ) AS DIFF |
public_review_platform | List all the tires businesses that are opened everyday. | tires businesses refers to category_name = 'Tires'; opened everyday refers to COUNT(distinct opening_time) = 7; | SELECT DISTINCT T2.business_id 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 Business_Hours AS T4 ON T3.business_id = T4.business_id WHERE T1.category_name = 'Tires' GROUP BY T2.business_id HAVING COUNT(day_id) = 7 |
public_review_platform | Which users become an elite in 2012? | in 2012 refers to actual_year = 2012; | SELECT DISTINCT T1.user_id FROM Elite AS T1 INNER JOIN Years AS T2 ON T1.year_id = T2.year_id WHERE T2.actual_year = 2012 |
public_review_platform | List the business ID of shopping business that have 4 stars ratings. | shopping business refers to category_name = 'Shopping'; 4 stars ratings refers to stars = 4 | SELECT T1.business_id FROM Business 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 = 'Shopping' AND T1.stars = 4 |
public_review_platform | How many business have low check-in on Sunday at 10AM? | on Sunday refers to day_of_week = 'Sunday'; low check-in at 10AM refers to label_time_10 = 'Low' | SELECT COUNT(T2.business_id) FROM Days AS T1 INNER JOIN Checkins AS T2 ON T1.day_id = T2.day_id WHERE T1.day_of_week = 'Sunday' AND T2.label_time_10 = 'Low' |
public_review_platform | How many businesses in Glendale are reviewed by user with the ID of 20241? | in Glendale refers to city = 'Glendale' | SELECT COUNT(T1.business_id) FROM Business AS T1 INNER JOIN Reviews AS T2 ON T1.business_id = T2.business_id WHERE T1.city = 'Glendale' AND T2.user_id = 20241 |
public_review_platform | State the locations of all Pet Services business. | location refers to city; Pet Services business refers to category_name = 'Pet Services' | SELECT T1.city FROM Business 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 = 'Pet Services' |
public_review_platform | How many photos type compliment given from users with high cool votes? | photos type compliment refers to compliment_type = 'photos'; high cool votes refers to review_votes_cool = 'High' | SELECT COUNT(T1.user_id) FROM Users AS T1 INNER JOIN Users_Compliments AS T2 ON T1.user_id = T2.user_id INNER JOIN Compliments AS T3 ON T2.compliment_id = T3.compliment_id INNER JOIN Reviews AS T4 ON T1.user_id = T4.user_id WHERE T3.compliment_type = 'photos' AND T4.review_votes_cool = 'High' |
public_review_platform | How many closed businesses that have more than 10 attributes? | closed refers to active = 'false'; more than 10 attributes refers to count(attribute_id) > 10 | SELECT COUNT(*) FROM Business WHERE business_id IN ( SELECT T1.business_id FROM Business AS T1 INNER JOIN Business_Attributes AS T2 ON T1.business_id = T2.business_id WHERE T1.active = 'false' GROUP BY T1.business_id HAVING COUNT(DISTINCT T2.attribute_id) > 10 ) |
public_review_platform | List the business located in Mesa that have alcohol attribute. | in Mesa refers to city = 'Mesa'; alcohol attribute refers to attribute_name = 'Alcohol' | SELECT T1.business_id FROM Business AS T1 INNER JOIN Business_Attributes AS T2 ON T1.business_id = T2.business_id INNER JOIN Attributes AS T3 ON T2.attribute_id = T3.attribute_id WHERE T1.city = 'Mesa' AND T3.attribute_name = 'Alcohol' |
public_review_platform | Based on business in Phoenix, calculate the percentage of business with low funny votes. | in Chandelier refers to city = 'Chandelier'; percentage = divide(count(business_id where review_votes_funny = 'Low'), count(business_id)); business with low funny votes refers to review_votes_funny = 'Low' | SELECT CAST(SUM(CASE WHEN T2.review_votes_funny = 'Low' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.business_id) FROM Business AS T1 INNER JOIN Reviews AS T2 ON T1.business_id = T2.business_id WHERE T1.city = 'Phoenix' |
public_review_platform | What is the ratio between business in shopping category and business in pets category? | ratio = divide(count(business_id where category_name = 'Shopping'), count(business_id where category_name = 'Pets')) | SELECT CAST(SUM(CASE WHEN T2.category_name = 'Shopping' THEN 1 ELSE 0 END) AS REAL) / SUM(CASE WHEN T2.category_name = 'Pets' THEN 1 ELSE 0 END) AS radio FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.category_id |
public_review_platform | How many businesses are registered in the database under 'Banks & Credit Unions' category? | category refers to category_name | SELECT COUNT(T2.business_id) FROM Categories AS T1 INNER JOIN Business_Categories AS T2 ON T1.category_id = T2.category_id WHERE T1.category_name = 'Banks & Credit Unions' |
public_review_platform | How many active businesses from Casa Grande are registered in the database? | active business refers to active = 'true'; Casa Grande refers to city = 'Casa Grande' | SELECT COUNT(business_id) FROM Business WHERE active = 'true' AND city = 'Casa Grande' |
public_review_platform | What time does the business with ID no.12 open on Monday? | open time refers to opening_time; on Monday refers to day_of_week = 'Monday'; business with ID no. refers to business_id
| SELECT T1.opening_time FROM Business_Hours AS T1 INNER JOIN Days AS T2 ON T1.day_id = T2.day_id WHERE T1.business_id = 12 AND T2.day_of_week = 'Monday' |
public_review_platform | How many businesses that are registered in the database can be attributed to 'Good for Kids'? | can be attributed to 'Good for Kids' refers to attribute_name = 'Good for Kids' and attribute_value = 'true' | SELECT COUNT(T2.business_id) FROM Attributes AS T1 INNER JOIN Business_Attributes AS T2 ON T1.attribute_id = T2.attribute_id WHERE T1.attribute_name = 'Good for Kids' AND T2.attribute_value = 'true' |
public_review_platform | Identify the most popular and appealing active business in Gilbert based on users' reviews. | most popular and appealing refers to review_count = 'High' and max(stars); active business refers to active = 'true'; in Gilbert refers to city = 'Gilbert' | SELECT business_id FROM Business WHERE city = 'Gilbert' AND active = 'true' AND review_count = 'High' ORDER BY stars DESC LIMIT 1 |
public_review_platform | Find the 5-star business in Ahwatukee, AZ and identify it's business category. | 5-star refers to stars = 5; in Ahwatukee refers to city = 'Ahwatukee'; business category refers to category_name | SELECT T1.business_id, T3.category_name FROM Business 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 T1.city = 'Ahwatukee' AND T1.stars = 5 |
public_review_platform | Among all closed businesses in Avondale, AZ what percent have obtained a 'wonderful experience' rating of the business. | closed business refers to active = 'false'; in Avondale refers to city = 'Avondale'; 'wonderful experience' rating refers to stars > 3; percentage = divide(count(business_id where stars > 3), count(business_id))*100% | SELECT CAST(SUM(CASE WHEN stars > 3 THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(stars) FROM Business WHERE city = 'Avondale' AND active = 'false' |
public_review_platform | Identify the user who has been yelping since 2004. Is he or she an Yelp Elite member? | has been yelping since 2004 refers to user_yelping_since_year = 2004 | SELECT DISTINCT T2.user_id FROM Users AS T1 INNER JOIN Elite AS T2 ON T1.user_id = T2.user_id WHERE T1.user_yelping_since_year = 2004 |
public_review_platform | Identify the percent of long reviews among all 5-star reviews given to businesses by the Yelp users. | percentage = divide(count(business_id where review_length = 'Long' and review_stars = 5), count(business_id)) * 100%; long reviews refers to review_length = 'Long'; 5-star review refers to review_stars = 5 | SELECT CAST(SUM(CASE WHEN review_length = 'Long' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(review_length) FROM Reviews WHERE review_stars = 5 |
public_review_platform | How many short tips were left for the business with ID no.2? | short tip refers to tip_length = 'Short'; business category refers to category_name | SELECT COUNT(business_id) FROM Tips WHERE business_id = 2 AND tip_length = 'Short' |
public_review_platform | Among all the users who received the high number of compliments, what percent received the 'cute' type of compliment. | high number of compliments refers to number_of_compliments = 'High'; percentage = divide(count(user_id where compliment_type = 'cute'), count(user_id))*100% | SELECT CAST(SUM(CASE WHEN T1.compliment_type = 'cute' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T2.user_id) FROM Compliments AS T1 INNER JOIN Users_Compliments AS T2 ON T1.compliment_id = T2.compliment_id WHERE T2.number_of_compliments = 'High' |
public_review_platform | Mention the number of businesses that have no any attribute. | have no attribute refers to attribute_value in( 'none', 'no', 'false') | SELECT COUNT(business_id) FROM Business_Attributes WHERE attribute_value IN ('none', 'no', 'false') |
public_review_platform | List out city name of businesses which have medium length of review. | medium length of review refers to review_length = 'Medium' | SELECT DISTINCT T1.city FROM Business AS T1 INNER JOIN Reviews AS T2 ON T1.business_id = T2.business_id WHERE T2.review_length = 'Medium' |
public_review_platform | Among the businesses which have short length of review, which one located in Phoenix? | short length of review refers to review_length = 'Short'; in Phoenix refers to city = 'Phoenix' | SELECT DISTINCT T1.business_id FROM Business AS T1 INNER JOIN Reviews AS T2 ON T1.business_id = T2.business_id WHERE T1.city = 'Phoenix' AND T2.review_length = 'Short' |
public_review_platform | Among the users whose fan is medium, how many users received high compliments from other users. | is medium refers to user_fans = 'Medium'; high compliments refers to number_of_compliments = 'High' | SELECT COUNT(T1.user_id) FROM Users AS T1 INNER JOIN Users_Compliments AS T2 ON T1.user_id = T2.user_id WHERE T2.number_of_compliments = 'High' AND T1.user_fans = 'Medium' |
public_review_platform | Among the users who received low compliments from other users, which users joined Yelp in 2012? | low compliments refers to number_of_compliments = 'Low'; joined Yelp in 2012 refers to user_yelping_since_year = 2012 | SELECT DISTINCT T2.user_id FROM Users AS T1 INNER JOIN Users_Compliments AS T2 ON T1.user_id = T2.user_id WHERE T1.user_yelping_since_year = 2012 AND T2.number_of_compliments = 'Low' |
public_review_platform | Among the businesses without attribute, how many businesses located in Gilbert? | without attribute refers to attribute_value = 'None'; in Gilbert refers to city = 'Gilbert' | SELECT COUNT(T2.business_id) FROM Business_Attributes AS T1 INNER JOIN Business AS T2 ON T1.business_id = T2.business_id WHERE T2.city = 'Gilbert' AND T1.attribute_value IN ('None', 'no', 'false') |
public_review_platform | Among the businesses with average rating, how many business has attribute of full_bar. | average rating refers to avg(stars); attribute of full_bar refers to attribute_value = 'full_bar' | SELECT COUNT(T1.business_id) FROM Business_Attributes AS T1 INNER JOIN Business AS T2 ON T1.business_id = T2.business_id WHERE T1.attribute_value = 'full_bar' |
public_review_platform | List out the state of businesses which have opening time at 1AM. | state refers to city | SELECT DISTINCT T1.state FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id WHERE T2.opening_time = '1AM' |
public_review_platform | List out the category name of business id 5. | SELECT T1.category_name FROM Categories AS T1 INNER JOIN Business_Categories AS T2 ON T1.category_id = T2.category_id WHERE T2.business_id = 5 | |
public_review_platform | List out the user id that has compliment type of photos. | compliment type of photos refers to compliment_type = 'photos' | SELECT T2.user_id FROM Compliments AS T1 INNER JOIN Users_Compliments AS T2 ON T1.compliment_id = T2.compliment_id WHERE T1.compliment_type = 'photos' |
public_review_platform | State the state of businesses which have closing time at 12AM. | state refers to city | SELECT DISTINCT T1.state FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id WHERE T2.closing_time = '12AM' |
public_review_platform | Among the businesses which have attribute of beer_and_wine, how many business located in Peoria? | attribute of beer_and_wine refers to attribute_value = 'beer_and_wine'; in Peoria refers to city = 'Peoria' | SELECT COUNT(T1.business_id) FROM Business_Attributes AS T1 INNER JOIN Business AS T2 ON T1.business_id = T2.business_id WHERE T2.city = 'Peoria' AND T1.attribute_value = 'beer_and_wine' |
public_review_platform | Among the users who received high compliments from other users, which users joined Yelp earliest? | high compliments refers to number_of_compliments = ' High'; joined Yelp earliest refers to min(user_yelping_since_year) | SELECT T2.user_id FROM Users AS T1 INNER JOIN Users_Compliments AS T2 ON T1.user_id = T2.user_id WHERE T2.number_of_compliments = 'High' AND T1.user_yelping_since_year = ( SELECT MIN(user_yelping_since_year) FROM Users ) |
public_review_platform | Which business ID has the most reviews? | the most reviews refer to MAX(user_id); | SELECT business_id FROM Reviews GROUP BY business_id ORDER BY COUNT(user_id) DESC LIMIT 1 |
public_review_platform | Which year has the most elite users? | year has the most elite users refers to year_id with MAX(user_id); | SELECT year_id FROM Elite GROUP BY year_id ORDER BY COUNT(user_id) DESC LIMIT 1 |
public_review_platform | How many 5 star businesses have uber review votes for funny? | businesses refer to business_id; review_stars = 5.0; review_votes_funny = 'uber'; | SELECT COUNT(business_id) FROM Reviews WHERE review_stars = 5 AND review_votes_funny = 'Uber' |
public_review_platform | How many users have uber review votes for funny from the fans? | users refer to user_id; review_votes_funny = 'uber'; | SELECT COUNT(DISTINCT user_id) FROM Reviews WHERE review_votes_funny = 'Uber' |
public_review_platform | Find out which business ID are opened all the time. | opened all the time refers to Business_Hours where day_id BETWEEN 1 and 7 and opening_time = closing_time; | SELECT DISTINCT business_id FROM Business_Hours WHERE day_id >= 1 AND day_id < 8 AND opening_time = closing_time |
public_review_platform | Does the length of the tip influence the number of likes for hotel and travel business category? | the longer the tip_length, the lesser the likes OR the longer the tip length the higher the likes; hotel and travel business category refers to category_name = 'Hotels & Travel'; | SELECT T3.tip_length, SUM(T3.likes) AS likes 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 T1.category_name = 'Hotels & Travel' GROUP BY T3.tip_length |
public_review_platform | What is the ratio of good to bad business star for a businesses that are opened all the time? | opened all the time refers to Business_Hours where day_id BETWEEN 1 and 7 and opening_time = closing_time; ratio can be computed as DIVIDE(COUNT(stars BETWEEN 3.5 and 5), COUNT(stars BETWEEN 1 and 2.5)); | SELECT CAST(SUM(CASE WHEN T1.stars BETWEEN 3.5 AND 5 THEN 1 ELSE 0 END) AS REAL) / SUM(CASE WHEN T1.stars BETWEEN 1 AND 2.5 THEN 1 ELSE 0 END) AS ratio FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id |
public_review_platform | How many businesses in Arizona having an average review less than 3 stars? | businesses in Arizona refer to business_id where state = 'Arizona'; average review less than 3 stars refers to AVG(review_stars) < 3.0; | SELECT COUNT(business_id) FROM Business WHERE business_id IN ( SELECT DISTINCT T1.business_id FROM Business AS T1 INNER JOIN Reviews AS T2 ON T1.business_id = T2.business_id WHERE T1.state = 'AZ' GROUP BY T1.business_id HAVING SUM(T2.review_stars) / COUNT(T2.user_id) < 3 ) |
public_review_platform | What is the percentage of user not becoming an elite user? | DIVIDE(SUBTRACT(COUNT(user_id), COUNT(Elite.user_id)), COUNT(user_id)) as percentage; | SELECT CAST((( SELECT COUNT(user_id) FROM Users ) - ( SELECT COUNT(DISTINCT user_id) FROM Elite )) AS REAL) * 100 / ( SELECT COUNT(user_id) FROM Users ) |
public_review_platform | What are the most common compliments types received by user with uber number of fans? | the most common compliments types refer to MAX(COUNT(compliment_id)); user_fans = 'uber'; | SELECT DISTINCT T3.compliment_type FROM Users AS T1 INNER JOIN Users_Compliments AS T2 ON T1.user_id = T2.user_id INNER JOIN Compliments AS T3 ON T2.compliment_id = T3.compliment_id WHERE T1.user_fans = 'Uber' |
public_review_platform | What is the average year needed by a user with uber fans to become an elite user? | AVG(user_yelping_since_year) where user_fans = 'uber'; | SELECT CAST(SUM(T2.year_id - T1.user_yelping_since_year) AS REAL) / COUNT(T1.user_id) FROM Users AS T1 INNER JOIN Elite AS T2 ON T1.user_id = T2.user_id WHERE T1.user_fans = 'Uber' |
public_review_platform | What is the average year for a user to be upgraded to elite user? | AVG(user_yelping_since_year) where user_id from Elite; | SELECT CAST(SUM(T2.year_id - T1.user_yelping_since_year) AS REAL) / COUNT(T1.user_id) FROM Users AS T1 INNER JOIN Elite AS T2 ON T1.user_id = T2.user_id |
public_review_platform | How many business are opened for more than 8 hour in Mesa and what is the percentage of the active businesses? | business are opened for more than 8 hours refer to business_id where SUBTRACT(closing_time, opening_time) > 8; DIVIDE(COUNT(business_id where active = 'true' and city = 'Mesa' and SUBTRACT(closing_time, opening_time) > 8), COUNT(business_id where city = 'Mesa' and SUBTRACT(closing_time, opening_time) > 8)) as percentage; | SELECT CAST(SUM(CASE WHEN T1.active = 'true' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.business_id) AS ACT FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id WHERE T1.city = 'Mesa' |
public_review_platform | How many active businesses are opened during late afternoon in the Phoenix city? List out the top 3 categories name for these businesses. | opened during late afternoon refers to Business_Hours where opening_time ≥ '5PM'; active businesses refer to business_id where active = 'true'; | SELECT DISTINCT T4.category_name 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.city = 'Phoenix' AND T1.opening_time >= '5PM' LIMIT 3 |
public_review_platform | Which user has done the most review on a business attributed to delivery? | the most reviews refer to MAX(business_id) where attribute_name = 'Delivery'; | SELECT T3.user_id FROM Attributes AS T1 INNER JOIN Business_Attributes AS T2 ON T1.attribute_id = T2.attribute_id INNER JOIN Reviews AS T3 ON T2.business_id = T3.business_id WHERE T1.attribute_name = 'Delivery' GROUP BY T3.user_id ORDER BY COUNT(T2.business_id) DESC LIMIT 1 |
public_review_platform | How many business ids have opening hours from 8AM to 6PM? | opening hours from 8AM to 6PM refer to Business_Hours where opening_time = '8AM' and closing_time = '6PM'; | SELECT DISTINCT business_id FROM Business_Hours WHERE opening_time = '8AM' AND closing_time = '6PM' |
public_review_platform | Provide business ids with opening hours 10AM on Saturday. | opening hours 10AM on Saturday refer to Business_Hours where opening_time = '10AM' and day_id = 6; | SELECT DISTINCT business_id FROM Business_Hours WHERE day_id = 6 AND opening_time = '10AM' |
public_review_platform | Indicate the business id and days which are opened from 8AM to 6PM. | opened from 8AM to 6PM refers to Business_Hours where opening_time = '8AM' and closing_time = '6PM'; days refer to day_id; | SELECT DISTINCT day_id FROM Business_Hours WHERE opening_time = '8AM' AND closing_time = '6PM' |
public_review_platform | How many businesses id are rated more than 4? | rated more than 4 refers to stars > 4; | SELECT COUNT(business_id) FROM Business WHERE stars > 4 |
public_review_platform | What are the categories of businesses that have opening time on Sunday? | categories of businesses refer to category_name; Sunday refers to day_of_week where day_id = 1; | 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_Hours AS T3 ON T2.business_id = T3.business_id INNER JOIN Days AS T4 ON T3.day_id = T4.day_id WHERE T4.day_of_week = 'Sunday' AND T3.opening_time <> '' |
public_review_platform | Please indicate the opening day of businesses whose category is pets. | category is pets refers to category_name = 'Pets'; opening day refers to day_id from Business_Hours and opening_time; | SELECT DISTINCT T4.day_of_week FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Business_Hours AS T3 ON T1.business_id = T3.business_id INNER JOIN Days AS T4 ON T3.day_id = T4.day_id WHERE T2.category_name = 'Pets' |
public_review_platform | Please indicate the closing hours and business days of the businesses with the category named Doctors. | closing hours refer to closing_time; business days refer to day_id from Business_Hours; | SELECT DISTINCT T3.opening_time, T3.day_id FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Business_Hours AS T3 ON T1.business_id = T3.business_id INNER JOIN Days AS T4 ON T3.day_id = T4.day_id WHERE T2.category_name = 'Doctors' |
public_review_platform | Among the working days from Monday to Saturday, which businesses with the category names work the most days? | days from Monday to Saturday refer to day_id between 2 and 7; work the most days can be computed as MAX(COUNT(category_name where day_id between 2 and 7)); | SELECT T2.category_name FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Business_Hours AS T3 ON T1.business_id = T3.business_id INNER JOIN Days AS T4 ON T3.day_id = T4.day_id GROUP BY T2.category_name ORDER BY COUNT(T3.day_id) DESC LIMIT 1 |
public_review_platform | Please indicate the business id have the closing time with the category of Arts & Entertainment on Sunday. | Sunday refers to day_of_week = 'Sunday' where day_id = 1; category of Arts & Entertainment refers to category_name = 'Arts & Entertainment'; | SELECT T1.business_id, T3.closing_time FROM Business_Categories AS T1 INNER JOIN Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Business_Hours AS T3 ON T1.business_id = T3.business_id INNER JOIN Days AS T4 ON T3.day_id = T4.day_id WHERE T2.category_name = 'Arts & Entertainment' AND T4.day_of_week = 'Sunday' |
public_review_platform | In businesses with a category of "DJs", how many businesses are rated less than 5? | category of "DJs" refers to category_name = 'DJs'; rated less than 5 refers to stars < 5; businesses refer to business_id; | SELECT COUNT(T1.business_id) FROM Business 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 = 'DJs' AND T1.stars < 5 |
public_review_platform | List active business ids with opening times of 7AM and closing times of 8PM. | opening times of 7AM and closing times of 8PM refer to Business_Hours where opening_time = '7AM' and closing_time = '8PM'; active business refers to business_id where active = 'true'; | SELECT DISTINCT T4.business_id FROM Categories AS T1 INNER JOIN Business_Categories AS T2 ON T1.category_id = T2.category_id INNER JOIN Business_Hours AS T3 ON T2.business_id = T3.business_id INNER JOIN Business AS T4 ON T3.business_id = T4.business_id WHERE T4.active = 'true' AND T3.opening_time = '7AM' AND T3.closing_time = '8PM' |
public_review_platform | How many businesses with the category named Stadiums & Arenas are rated highest? | rated highest refers to MAX(stars); category_name = 'Stadiums & Arenas'; | SELECT COUNT(T1.business_id) 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 = 'Stadiums & Arenas' AND T3.stars = ( SELECT MAX(stars) FROM Business ) |
public_review_platform | How many category id have low review count and rating more than 2? | rating more than 2 refers to stars > 2; | SELECT COUNT(DISTINCT T1.category_id) 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 WHERE T3.review_count = 'Low' AND T3.stars > 2 |
public_review_platform | Among the active businesses in Arizona, how many businesses work after 12PM? | active businesses in Arizona refer to business_id where state = 'Arizona' and active = 'true'; work after 12PM refer to opening_time > '12PM'; | 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' |
public_review_platform | Please provide the name of businesses with user id "16328". | name of business refers to category_name; | 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 |
public_review_platform | How many businesses have the category named food? List those businesses and find the percentage of businesses with less than 2 stars. | 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; | 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' |
public_review_platform | Calculate the percentage of businesses with the category name food that are open from 7AM to 8PM in the businesses with the same time. | 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; | 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 |
public_review_platform | Write down the number of running business with each review count in Cave Creek city. | 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'; | 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' |
public_review_platform | Calculate the yearly average user who started using Yelp from the year of 2005 to 2014. | avg(user_id) where user_yelping_since_year BETWEEN '2005' AND '2014'; | SELECT AVG(user_id) FROM Users WHERE user_yelping_since_year >= 2005 AND user_yelping_since_year <= 2015 |
public_review_platform | What is the active and inactive ratio of the business with the review count of low. | DIVIDE(COUNT(business_id where review_count = 'Low' and active = 'true'), COUNT(business_id where review_count = 'Low' and active = 'false')); | 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' |
public_review_platform | List any five of user ID who became elite user in 2006. | year_id = '2006'; | SELECT user_id FROM Elite WHERE year_id = 2006 LIMIT 5 |
public_review_platform | Write down the any five of ID and name of category that starts with alphabet "P". | category that starts with alphabet "P" refers to category_name like 'P%'; | SELECT category_id, category_name FROM Categories WHERE category_name LIKE 'P%' LIMIT 5 |
public_review_platform | Provide the list of user ID along with review star of which has the review length of medium with business ID of 35. | ; | SELECT user_id, review_stars FROM Reviews WHERE business_id = 15 AND review_length = 'Medium' |
public_review_platform | List down the business ID and attribute value of the attribute name of "payment_types_visa". | 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' | |
public_review_platform | Describe ID and active status of the business under category of "Diagnostic Imaging". | ID refers to business_id; category of "Diagnostic Imaging" refers to category_name = 'Diagnostic Imaging'; | SELECT T2.business_id, T3.active 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 WHERE T1.category_name = 'Diagnostic Imaging' |
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