db_id
stringclasses 69
values | question
stringlengths 24
325
| evidence
stringlengths 0
673
| SQL
stringlengths 23
804
| question_id
int64 0
9.43k
| difficulty
stringclasses 1
value |
|---|---|---|---|---|---|
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'
| 4,000 | |
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'
| 4,001 | |
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
| 4,002 | |
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'
| 4,003 | |
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'
| 4,004 | |
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'
| 4,005 | |
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'
| 4,006 | |
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
| 4,007 | |
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
| 4,008 | |
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'
| 4,009 | |
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
| 4,010 | |
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
| 4,011 | |
public_review_platform
|
Among all the users with the average ratings of at least 4 and above of all reviews, calculate the percent that have no fans or followers.
|
average ratings of at least 4 refers to user_average_stars > = 4; no fans or followers refers to user_fans = 'None'; percentage = divide(count(user_id where user_average_stars > = 4 and user_fans = 'None'), sum(user_id where user_average_stars > = 4))*100%
|
SELECT CAST(SUM(CASE WHEN user_fans = 'None' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(user_id) FROM Users WHERE user_average_stars >= 4
| 4,012 | |
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'
| 4,013 | |
public_review_platform
|
Find the Yelp user with the average 5-star rating of all reviews who has been yelping the longest.
|
Yelp user refers to user_id; average 5-star rating refers to user_average_stars = 5; yelping the longest refers to min(user_yelping_since_year)
|
SELECT user_id FROM Users WHERE user_average_stars = 5 ORDER BY user_yelping_since_year ASC LIMIT 1
| 4,014 | |
public_review_platform
|
Identify the operating hours of businesses in Black Canyon City with review count greater than average.
|
operating hours refers to opening_time closing_time on day_id; in Black Canyon City refers to city = 'Black Canyon City'; greater than average refers to review_count > AVG(T1.review_count)
|
SELECT T2.opening_time, T2.closing_time FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id INNER JOIN Days AS T3 ON T2.day_id = T3.day_id WHERE T1.city = 'Black Canyon City' GROUP BY t2.business_id HAVING T1.review_count > AVG(T1.review_count)
| 4,015 | |
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'
| 4,016 | |
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')
| 4,017 | |
public_review_platform
|
What are the opening and closing time of business id 1 for day id 2?
|
false
|
SELECT opening_time, closing_time FROM Business_Hours WHERE business_id = 1 AND day_id = 2
| 4,018 | |
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'
| 4,019 | |
public_review_platform
|
What is the closing time of business id 4 on Sunday?
|
on Sunday refers to day_of_week = 'Sunday'
|
SELECT T2.closing_time FROM Days AS T1 INNER JOIN Business_Hours AS T2 ON T1.day_id = T2.day_id WHERE T1.day_of_week = 'Sunday' AND T2.business_id = 4
| 4,020 | |
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'
| 4,021 | |
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'
| 4,022 | |
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'
| 4,023 | |
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')
| 4,024 | |
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'
| 4,025 | |
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'
| 4,026 | |
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
| 4,027 | ||
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'
| 4,028 | |
public_review_platform
|
Calculate the percentage of medium tip length in the list. List out the time when users of medium tip length join Yelp.
|
medium tip length refers to tip_length = 'Medium'; percentage = divide(count(tips where tip_length = 'Medium'), count(tips))*100%; the time when users join Yelp refers to user_yelping_since_year
|
SELECT CAST(SUM(CASE WHEN T1.tip_length = 'Medium' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.tip_length), T2.user_yelping_since_year FROM Tips AS T1 INNER JOIN Users AS T2 ON T1.user_id = T2.user_id
| 4,029 | |
public_review_platform
|
Calculate the percentage of businesses who located in Mesa. What is attribute value of these businesses.
|
percentage = divide(count(business where city = 'Mesa'), count(business)) * 100%
|
SELECT CAST(COUNT(T1.city) AS REAL) * 100 / ( SELECT COUNT(business_id) FROM Business ), T2.attribute_value FROM Business AS T1 INNER JOIN Business_Attributes AS T2 ON T1.business_id = T2.business_id WHERE T1.city = 'Mesa'
| 4,030 | |
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'
| 4,031 | |
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'
| 4,032 | |
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 )
| 4,033 | |
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
| 4,034 | |
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
| 4,035 | |
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'
| 4,036 | |
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'
| 4,037 | |
public_review_platform
|
Which business ID have the shortest business operating hours?
|
the shortest business operating hours refer to MIN(SUBTRACT(closing_time, opening_time));
|
SELECT business_id FROM Business_Hours ORDER BY closing_time - opening_time LIMIT 1
| 4,038 | |
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
| 4,039 | |
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
| 4,040 | |
public_review_platform
|
How many users manage to get uber votes for all of the review category? Find out what are the user average star.
|
users refer to user_id; uber votes for all of the review category refer to review_votes_funny = 'uber' AND review_votes_useful = 'uber' AND review_votes_cool = 'uber';
|
SELECT COUNT(T2.user_id) AS USER_IDS, T2.user_average_stars FROM Reviews AS T1 INNER JOIN Users AS T2 ON T1.user_id = T2.user_id WHERE T1.review_votes_funny = 'Uber' AND T1.review_votes_useful = 'Uber' AND T1.review_votes_cool = 'Uber'
| 4,041 | |
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
| 4,042 | |
public_review_platform
|
List out 10 business ID that are being reviewed the most by users and list out what are top 3 business categories.
|
being reviewed the most refers to MAX(user_id); business categories refer to category_name;
|
SELECT T2.business_id, T3.category_name FROM Reviews 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 GROUP BY T2.business_id ORDER BY COUNT(T1.user_id) DESC LIMIT 10
| 4,043 | |
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 )
| 4,044 | |
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 )
| 4,045 | |
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'
| 4,046 | |
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'
| 4,047 | |
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
| 4,048 | |
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'
| 4,049 | |
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
| 4,050 | |
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
| 4,051 | |
public_review_platform
|
What is the average number of reviews written for active businesses that operate not more than 30 hours a week?
|
avg(user_id) where active = 'true' and SUM(SUBTRACT(closing_time, opening_time)) < 30;
|
SELECT AVG(T3.user_id) FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id INNER JOIN Reviews AS T3 ON T1.business_id = T3.business_id WHERE T1.active = 'true' GROUP BY T2.closing_time - T2.opening_time HAVING SUM(T2.closing_time - T2.opening_time) < 30
| 4,052 | |
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'
| 4,053 | |
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'
| 4,054 | |
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'
| 4,055 | |
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
| 4,056 | |
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 <> ''
| 4,057 | |
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'
| 4,058 | |
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'
| 4,059 | |
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
| 4,060 | |
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'
| 4,061 | |
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
| 4,062 | |
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'
| 4,063 | |
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 )
| 4,064 | |
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
| 4,065 | |
public_review_platform
|
Which businesses with the category name Accessories have opening hours before 7AM?
|
opening hours before 7AM refer to opening_time < '7AM'; businesses refer to business_id;
|
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'
| 4,066 | |
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'
| 4,067 | |
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
| 4,068 | |
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'
| 4,069 | |
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
| 4,070 | |
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'
| 4,071 | |
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
| 4,072 | |
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'
| 4,073 | |
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
| 4,074 | |
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
| 4,075 | |
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'
| 4,076 | |
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'
| 4,077 | ||
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'
| 4,078 | |
public_review_platform
|
Mention the user ID and their year of joining Yelp who had great experience on business ID 143.
|
year of joining Yelp refers to user_yelping_since_year; great experience refers to Reviews where review_stars = 5;
|
SELECT T2.user_id, T2.user_yelping_since_year FROM Reviews AS T1 INNER JOIN Users AS T2 ON T1.user_id = T2.user_id WHERE T1.business_id = 143 AND T1.review_stars = 5
| 4,079 | |
public_review_platform
|
Among the user ID with number in compliment of uber on profile, list any 5 user ID and the year when they join Yelp.
|
when join Yelp refers to user_yelping_since_year; compliment_type = 'profile'; number_of_compliments = 'Uber';
|
SELECT T3.user_id, T3.user_yelping_since_year 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 T1.compliment_type = 'profile' AND T2.number_of_compliments = 'Uber' LIMIT 5
| 4,080 | |
public_review_platform
|
List the user ID, business ID with review length of the business which received the most likes in tips.
|
business which received the most likes refers to business_id where MAX(likes);
|
SELECT T1.user_id, T1.business_id, T2.review_length FROM Tips AS T1 INNER JOIN Reviews AS T2 ON T1.business_id = T2.business_id ORDER BY T1.likes DESC LIMIT 1
| 4,081 | |
public_review_platform
|
Among the elite users of 10 consecutive year from 2005 to 2014, list down the user ID and their number of compliment on photos.
|
from 2005 to 2014 refers to year_id BETWEEN 2005 AND 2014; compliment_type = 'photos';
|
SELECT T2.user_id, T2.number_of_compliments FROM Compliments AS T1 INNER JOIN Users_Compliments AS T2 ON T1.compliment_id = T2.compliment_id INNER JOIN Elite AS T3 ON T2.user_id = T3.user_id WHERE T3.year_id BETWEEN 2005 AND 2014 AND T1.compliment_type = 'photos'
| 4,082 | |
public_review_platform
|
Calculate the percentage of business which opened on Sunday from 9AM to 9PM based on the number of business opened on Sunday.
|
Sunday refers to day_of_week = 'Sunday' where day_id = 1; opened from 9AM to 9PM refers to Business_Hours where opening_time = '9AM' and closing_time = '9PM'; DIVIDE(COUNT(opening_time = '9AM' and closing_time = '9PM' and day_of_week = 'Sunday'), COUNT(opening_time = NOT NULL and closing_time = NOT NULL and day_of_week = 'Sunday')) as percentage;
|
SELECT CAST(SUM(CASE WHEN T2.opening_time = '9AM' AND T2.closing_time = '9PM' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T1.day_id) FROM Days AS T1 INNER JOIN Business_Hours AS T2 ON T1.day_id = T2.day_id WHERE T1.day_of_week = 'Sunday'
| 4,083 | |
public_review_platform
|
Write down the ID and opening day of a week for the business which are running in Black Canyon City.
|
running refers to active = 'true'; opening day of a week means days of the week when business is open;
|
SELECT T2.business_id, T3.day_of_week FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id INNER JOIN Days AS T3 ON T2.day_id = T3.day_id WHERE T1.city = 'Black Canyon City' AND T1.active = 'true'
| 4,084 | |
public_review_platform
|
Within the user who joined Yelp in 2004, explore the user ID with average star of 5 and it's review length on the business.
|
user who joined Yelp in 2004 refers to user_id where user_yelping_since_year = 2014; user_average_stars = 5;
|
SELECT T2.user_id, T2.review_length FROM Users AS T1 INNER JOIN Reviews AS T2 ON T1.user_id = T2.user_id WHERE T1.user_yelping_since_year = 2004 AND T1.user_average_stars = 5
| 4,085 | |
public_review_platform
|
Which business ID received the review of 4 star and above by 65% of user? Describe their active status and city.
|
review of 4 star and above refers to stars > 4; DIVIDE(SUM(stars > 4), COUNT(business_id)) = 0.65;
|
SELECT DISTINCT T2.business_id, T2.city FROM Reviews AS T1 INNER JOIN Business AS T2 ON T1.business_id = T2.business_id WHERE T1.review_stars >= 4 AND ( SELECT CAST(( SELECT COUNT(DISTINCT T1.user_id) FROM Reviews AS T1 INNER JOIN Business AS T2 ON T1.business_id = T2.business_id WHERE T1.review_stars >= 4 ) AS REAL) * 100 / ( SELECT COUNT(user_id) FROM Users ) > 65 )
| 4,086 | |
public_review_platform
|
Calculate the difference between running business in Glendale City and Mesa City.
|
running business refers to business where active = 'true';
|
SELECT SUM(CASE WHEN city = 'Glendale' THEN 1 ELSE 0 END) - SUM(CASE WHEN city = 'Mesa' THEN 1 ELSE 0 END) AS diff FROM Business WHERE active = 'true'
| 4,087 | |
public_review_platform
|
How many likes did short comment left by users who joined in 2010 get?
|
short comment refers to tip_length = 'Short'; users who joined in 2010 refer to user_id where user_yelping_since_year = 2010;
|
SELECT SUM(T2.likes) FROM Users AS T1 INNER JOIN Tips AS T2 ON T1.user_id = T2.user_id WHERE T1.user_yelping_since_year = 2010
| 4,088 | |
public_review_platform
|
For users with average ratings of 3, what kind of tip length they mostly left?
|
average ratings of 3 refer to user_average_stars = 3; kind of tip length they mostly left refers to tip_length where MAX(COUNT(user_id));
|
SELECT T2.tip_length FROM Users AS T1 INNER JOIN Tips AS T2 ON T1.user_id = T2.user_id WHERE T1.user_average_stars = 3 GROUP BY T2.tip_length ORDER BY COUNT(T2.tip_length) DESC LIMIT 1
| 4,089 | |
public_review_platform
|
Sum up the likes get by short reviews on businesses located in City Goodyear.
|
short reviews refer to tip_length = 'Short';
|
SELECT SUM(T2.likes) AS likes FROM Business AS T1 INNER JOIN Tips AS T2 ON T1.business_id = T2.business_id WHERE T1.city = 'Goodyear'
| 4,090 | |
public_review_platform
|
For businesses with long length reviews, which state are they located?
|
businesses with long length tips refer to business_id where tip_length = 'Long';
|
SELECT DISTINCT T1.state FROM Business AS T1 INNER JOIN Tips AS T2 ON T1.business_id = T2.business_id WHERE T2.tip_length = 'Long'
| 4,091 | |
public_review_platform
|
How much time do businesses in El Mirage City, AZ State operate in average daily?
|
how much time does this business open refers to SUBTRACT(closing_time, opening_time); DIVIDE(SUM(SUBTRACT(closing_time, opening_time)), SUM(Business.business_id))
|
SELECT SUM(T2.closing_time - T2.opening_time) FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id WHERE T1.city = 'El Mirage' AND T1.state = 'AZ'
| 4,092 | |
public_review_platform
|
List down the closing day of businesses located at SC State.
|
closing day refers to SUBTRACT(days.day_id, business_Hours.day_id)
|
SELECT T3.day_id - T2.day_id FROM Business AS T1 INNER JOIN Business_Hours AS T2 ON T1.business_id = T2.business_id INNER JOIN Days AS T3 ON T2.day_id = T3.day_id WHERE T1.state = 'SC'
| 4,093 | |
public_review_platform
|
List down the category of businesses whose stars ratings are 5.
|
category of businesses refers to category_name; stars ratings are 5 refers to stars = 5
|
SELECT DISTINCT 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.stars = 5
| 4,094 | |
public_review_platform
|
What are the states of businesses with attribute of beer and wine located?
|
with attribute of beer and wine refers to attribute_value = 'beer_and_wine';
|
SELECT DISTINCT T2.state FROM Business_Attributes AS T1 INNER JOIN Business AS T2 ON T1.business_id = T2.business_id WHERE T1.attribute_value = 'beer_and_wine'
| 4,095 | |
public_review_platform
|
How many user's compliment in photo has medium in number?
|
user's compliment in photo refers to compliment_type = 'photo'; photo has medium in number refers to number_of_compliments = 'Medium'
|
SELECT COUNT(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' AND T2.number_of_compliments = 'Medium'
| 4,096 | |
public_review_platform
|
Among businesses with "Wi-Fi" attribute, which businesses id are located at SC State?
|
"Wi-Fi" attribute refers to attribute_name = 'Wi-Fi' AND attribute_value = 'true'
|
SELECT T3.business_id 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 = 'Wi-Fi' AND T2.attribute_value = 'true' AND T3.state = 'SC'
| 4,097 | |
public_review_platform
|
Sum up the number of business with "ambience_romantic" attribute.
|
"ambience_romantic" attribute refers to attribute_name = 'ambience_romantic' 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 = 'ambience_romantic' AND T2.attribute_value = 'true'
| 4,098 | |
public_review_platform
|
What is the percentage of businesses with "Good for Kids" attribute over the other attributes?
|
"Good for Kids" attribute refers to attribute_name = 'Good for Kids' AND attribute_value = 'true'; Calculation = DIVIDE(SUM(attribute_name = 'Good for Kids' AND attribute_value = 'true')), SUM(business_id) * 100
|
SELECT CAST(SUM(CASE WHEN attribute_name = 'Good for Kids' THEN 1 ELSE 0 END) AS REAL) * 100 / COUNT(T2.business_id) FROM Attributes AS T1 INNER JOIN Business_Attributes AS T2 ON T1.attribute_id = T2.attribute_id WHERE T2.attribute_value = 'true'
| 4,099 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.