db_id stringclasses 146 values | question stringlengths 3 224 | sql stringlengths 18 577 | database_schema stringclasses 146 values |
|---|---|---|---|
yelp | List all the restaurant rated more than 3.5 | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.rating > 3.5 AND t2.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | find all cities which has a " Taj Mahal " restaurant | SELECT t1.city FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.name = "Taj Mahal" AND t2.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | list all the reviews by Niloofar | SELECT t1.text FROM USER AS t2 JOIN review AS t1 ON t2.user_id = t1.user_id WHERE t2.name = "Niloofar"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | list all the businesses which have a review by Niloofar | SELECT t1.name FROM review AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN USER AS t3 ON t3.user_id = t2.user_id WHERE t3.name = "Niloofar"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | list all the businesses which Niloofar rated 5 | SELECT t1.name FROM review AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN USER AS t3 ON t3.user_id = t2.user_id WHERE t2.rating = 5 AND t3.name = "Niloofar"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | List all the reviews by Michelle for Italian restaurant | SELECT t4.text FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN category AS t3 ON t3.business_id = t1.business_id JOIN review AS t4 ON t4.business_id = t1.business_id JOIN USER AS t5 ON t5.user_id = t4.user_id WHERE t2.category_name = "Italian" AND t3.category_name = "category_category_name1" AND t5.name = "Michelle"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | find the number of reviews written for " Cafe Zinho " restaurant in Texas | SELECT COUNT ( DISTINCT t3.text ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN review AS t3 ON t3.business_id = t1.business_id WHERE t1.name = "Cafe Zinho" AND t1.state = "Texas" AND t2.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | List all 5 star Italian restaurant | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN category AS t3 ON t3.business_id = t1.business_id WHERE t1.rating = 5 AND t2.category_name = "Italian" AND t3.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | List all the neighbourhoods with Italian restaurant in Madison | SELECT t1.neighbourhood_name FROM category AS t3 JOIN business AS t2 ON t3.business_id = t2.business_id JOIN category AS t4 ON t4.business_id = t2.business_id JOIN neighbourhood AS t1 ON t1.business_id = t2.business_id WHERE t2.city = "Madison" AND t3.category_name = "Italian" AND t4.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | List all the neighbourhoods with Italian restaurant rated less than 2.5 in Madison | SELECT t1.neighbourhood_name FROM category AS t3 JOIN business AS t2 ON t3.business_id = t2.business_id JOIN category AS t4 ON t4.business_id = t2.business_id JOIN neighbourhood AS t1 ON t1.business_id = t2.business_id WHERE t2.city = "Madison" AND t2.rating < 2.5 AND t3.category_name = "Italian" AND t4.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | find all the restaurant in Pennsylvania | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.state = "Pennsylvania" AND t2.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | List all businesses that are restaurant in Pennsylvania . | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.state = "Pennsylvania" AND t2.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all the reviews for all Pet Groomers with more than 100 reviews | SELECT t3.text FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN review AS t3 ON t3.business_id = t1.business_id WHERE t1.review_count > 100 AND t2.category_name = "Pet Groomers"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | What are all the breweries in " Los Angeles " ? | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.city = "Los Angeles" AND t2.category_name = "breweries"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all breweries in Los Angeles | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.city = "Los Angeles" AND t2.category_name = "breweries"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all breweries in " Los Angeles " | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.city = "Los Angeles" AND t2.category_name = "breweries"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all users who reviewed restaurant " Mesa Grill " | SELECT t4.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN review AS t3 ON t3.business_id = t1.business_id JOIN USER AS t4 ON t4.user_id = t3.user_id WHERE t1.name = "Mesa Grill" AND t2.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | List the addresses of all Walmart in " Los Angeles " | SELECT full_address FROM business WHERE city = "Los Angeles" AND name = "Walmart"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all restaurant reviewed by Patrick in " Dallas " | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN review AS t3 ON t3.business_id = t1.business_id JOIN USER AS t4 ON t4.user_id = t3.user_id WHERE t1.city = "Dallas" AND t2.category_name = "restaurant" AND t4.name = "Patrick"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Which restaurant in Dallas were reviewed by user Patrick ? | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN review AS t3 ON t3.business_id = t1.business_id JOIN USER AS t4 ON t4.user_id = t3.user_id WHERE t1.city = "Dallas" AND t2.category_name = "restaurant" AND t4.name = "Patrick"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all Bars reviewed by Patrick | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN review AS t3 ON t3.business_id = t1.business_id JOIN USER AS t4 ON t4.user_id = t3.user_id WHERE t2.category_name = "Bars" AND t4.name = "Patrick"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all Bars reviewed by Patrick with at least 3 stars | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN review AS t3 ON t3.business_id = t1.business_id JOIN USER AS t4 ON t4.user_id = t3.user_id WHERE t1.rating >= 3 AND t2.category_name = "Bars" AND t4.name = "Patrick"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all users who have written tips for " Barrio Cafe " in 2015 | SELECT t3.name FROM tip AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN USER AS t3 ON t3.user_id = t2.user_id WHERE t1.name = "Barrio Cafe" AND t2.year = 2015; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all businesses in Texas with a rating below 2 | SELECT name FROM business WHERE rating < 2 AND state = "Texas"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all restaurant Seafood in Los Angeles | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN category AS t3 ON t3.business_id = t1.business_id WHERE t1.city = "Los Angeles" AND t2.category_name = "Seafood" AND t3.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | List all the Seafood restaurant in " Los Angeles " | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN category AS t3 ON t3.business_id = t1.business_id WHERE t1.city = "Los Angeles" AND t2.category_name = "Seafood" AND t3.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all restaurant that serve Seafood in " Los Angeles " | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN category AS t3 ON t3.business_id = t1.business_id WHERE t1.city = "Los Angeles" AND t2.category_name = "Seafood" AND t3.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all reviews by Patrick with a rating above 4 | SELECT t1.text FROM USER AS t2 JOIN review AS t1 ON t2.user_id = t1.user_id WHERE t1.rating > 4 AND t2.name = "Patrick"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all Apple Store in " Los Angeles " | SELECT business_id FROM business WHERE city = "Los Angeles" AND name = "Apple Store"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all Dallas restaurant with a rating above 4.5 | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.city = "Dallas" AND t1.rating > 4.5 AND t2.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | What neighbourhood is restaurant " Flat Top Grill " in ? | SELECT t1.neighbourhood_name FROM category AS t3 JOIN business AS t2 ON t3.business_id = t2.business_id JOIN neighbourhood AS t1 ON t1.business_id = t2.business_id WHERE t2.name = "Flat Top Grill" AND t3.category_name = "category_category_name0"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all tips about " Vintner Grill " that received more than 9 likes | SELECT t2.text FROM tip AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.name = "Vintner Grill" AND t2.likes > 9; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all reviews about " Kabob Palace " in year 2014 | SELECT t2.text FROM review AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.name = "Kabob Palace" AND t2.year = 2014; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all users who have written tips about businesses in Dallas | SELECT t3.name FROM tip AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN USER AS t3 ON t3.user_id = t2.user_id WHERE t1.city = "Dallas"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all cities in Texas in which there is a restaurant called " MGM Grand Buffet " | SELECT t1.city FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.name = "MGM Grand Buffet" AND t1.state = "Texas" AND t2.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find the users who have given tips on Pet Groomers | SELECT t4.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN tip AS t3 ON t3.business_id = t1.business_id JOIN USER AS t4 ON t4.user_id = t3.user_id WHERE t2.category_name = "Pet Groomers"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all tips for " Cafe Zinho " in Texas . | SELECT t2.text FROM tip AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.name = "Cafe Zinho" AND t1.state = "Texas"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | List all users who reviewed businesses that are restaurant . | SELECT t4.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN review AS t3 ON t3.business_id = t1.business_id JOIN USER AS t4 ON t4.user_id = t3.user_id WHERE t2.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | List all tips for " Cafe Zinho " in Pennsylvania in 2010 . | SELECT t2.text FROM tip AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.name = "Cafe Zinho" AND t1.state = "Pennsylvania" AND t2.year = 2010; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | List all users who reviewed businesses that are restaurant in 2010 . | SELECT t4.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN review AS t3 ON t3.business_id = t1.business_id JOIN USER AS t4 ON t4.user_id = t3.user_id WHERE t2.category_name = "restaurant" AND t3.year = 2010; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all the tips from a user who has written a review in 2012 | SELECT t2.text FROM USER AS t3 JOIN review AS t1 ON t3.user_id = t1.user_id JOIN tip AS t2 ON t3.user_id = t2.user_id WHERE t1.year = 2012; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all reviews for businesses rated 2.5 | SELECT t2.text FROM review AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.rating = 2.5; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | find the number of escape games in Madison | SELECT COUNT ( DISTINCT t1.name ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.city = "Madison" AND t2.category_name = "escape games"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | What is the number of escape games in Madison | SELECT COUNT ( DISTINCT t1.name ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.city = "Madison" AND t2.category_name = "escape games"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many escape games exist in Madison | SELECT COUNT ( DISTINCT t1.name ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.city = "Madison" AND t2.category_name = "escape games"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | What is the number of escape games in " Madison " ? | SELECT COUNT ( DISTINCT t1.name ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.city = "Madison" AND t2.category_name = "escape games"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many escape games are there in Madison ? | SELECT COUNT ( DISTINCT t1.name ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.city = "Madison" AND t2.category_name = "escape games"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | find the number of restaurant rated more than 3.5 | SELECT COUNT ( DISTINCT t1.name ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.rating > 3.5 AND t2.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | find the total checkins in Moroccan restaurant in " Los Angeles " | SELECT SUM ( t4.count ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN category AS t3 ON t3.business_id = t1.business_id JOIN checkin AS t4 ON t4.business_id = t1.business_id WHERE t1.city = "Los Angeles" AND t2.category_name = "restaurant" AND t3.category_name = "Moroccan"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | find the total checkins in Moroccan restaurant in " Los Angeles " on Friday | SELECT SUM ( t4.count ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN category AS t3 ON t3.business_id = t1.business_id JOIN checkin AS t4 ON t4.business_id = t1.business_id WHERE t1.city = "Los Angeles" AND t2.category_name = "Moroccan" AND t3.category_name = "restaurant" AND t4.day = "Friday"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | find the total checkins in Moroccan restaurant in " Los Angeles " per day | SELECT t4.day , SUM ( t4.count ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN category AS t3 ON t3.business_id = t1.business_id JOIN checkin AS t4 ON t4.business_id = t1.business_id WHERE t1.city = "Los Angeles" AND t2.category_name = "Moroccan" AND t3.category_name = "restaurant" GROUP BY t4.day; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | find the total checkins in Italian Delis in each state on Sunday | SELECT t1.state , SUM ( t4.count ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN category AS t3 ON t3.business_id = t1.business_id JOIN checkin AS t4 ON t4.business_id = t1.business_id WHERE t2.category_name = "Italian" AND t3.category_name = "Delis" AND t4.day = "Sunday" GROUP BY t1.state; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many reviews has Niloofar written in 2015 | SELECT COUNT ( DISTINCT t1.text ) FROM USER AS t2 JOIN review AS t1 ON t2.user_id = t1.user_id WHERE t1.year = 2015 AND t2.name = "Niloofar"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | what is the average rating given in Michelle reviews | SELECT AVG ( t1.rating ) FROM USER AS t2 JOIN review AS t1 ON t2.user_id = t1.user_id WHERE t2.name = "Michelle"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | What is the number of checkins for " Cafe Zinho " on Friday | SELECT t2.count FROM checkin AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.name = "Cafe Zinho" AND t2.day = "Friday"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | how many users reviewed " Sushi Too " in Pittsburgh | SELECT COUNT ( DISTINCT t3.name ) FROM review AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN USER AS t3 ON t3.user_id = t2.user_id WHERE t1.city = "Pittsburgh" AND t1.name = "Sushi Too"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | What is the number of restaurant in Pittsburgh rated 4.5 | SELECT COUNT ( DISTINCT t1.name ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.city = "Pittsburgh" AND t1.rating = 4.5 AND t2.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many tips have been written in 2015 | SELECT COUNT ( DISTINCT text ) FROM tip WHERE YEAR = 2015; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | What is the total likes on tips from Niloofar | SELECT SUM ( t1.likes ) FROM USER AS t2 JOIN tip AS t1 ON t2.user_id = t1.user_id WHERE t2.name = "Niloofar"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | What is the total likes on tips about " Cafe Zinho " | SELECT SUM ( t2.likes ) FROM tip AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.name = "Cafe Zinho"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | What is the total likes on tips from Niloofar about " Cafe Zinho " | SELECT SUM ( t2.likes ) FROM tip AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN USER AS t3 ON t3.user_id = t2.user_id WHERE t1.name = "Cafe Zinho" AND t3.name = "Niloofar"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many tips has Michelle written in 2010 | SELECT COUNT ( DISTINCT t1.text ) FROM USER AS t2 JOIN tip AS t1 ON t2.user_id = t1.user_id WHERE t1.year = 2010 AND t2.name = "Michelle"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Return me the number of tips that are written by Michelle in 2010 . | SELECT COUNT ( DISTINCT t1.text ) FROM USER AS t2 JOIN tip AS t1 ON t2.user_id = t1.user_id WHERE t1.year = 2010 AND t2.name = "Michelle"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many tips has Michelle written in April | SELECT COUNT ( DISTINCT t1.text ) FROM USER AS t2 JOIN tip AS t1 ON t2.user_id = t1.user_id WHERE t1.month = "April" AND t2.name = "Michelle"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | what is the number of restaurant in Texas | SELECT COUNT ( DISTINCT t1.name ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.state = "Texas" AND t2.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many Bars in " Dallas " have a rating above 3.5 ? | SELECT COUNT ( DISTINCT t1.name ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.city = "Dallas" AND t1.rating > 3.5 AND t2.category_name = "Bars"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many Bars in Dallas have a rating above 3.5 ? | SELECT COUNT ( DISTINCT t1.name ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.city = "Dallas" AND t1.rating > 3.5 AND t2.category_name = "Bars"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many people reviewed the restaurant " Texas de Brazil " in Dallas Texas ? | SELECT COUNT ( DISTINCT t4.name ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN review AS t3 ON t3.business_id = t1.business_id JOIN USER AS t4 ON t4.user_id = t3.user_id WHERE t1.city = "Dallas" AND t1.name = "Texas de Brazil" AND t1.state = "Texas" AND t2.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many people reviewed " Bistro Di Napoli " in 2015 ? | SELECT COUNT ( DISTINCT t3.name ) FROM review AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN USER AS t3 ON t3.user_id = t2.user_id WHERE t1.name = "Bistro Di Napoli" AND t2.year = 2015; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many restaurant are there in the Hazelwood district of Dallas ? | SELECT COUNT ( DISTINCT t1.name ) FROM category AS t3 JOIN business AS t1 ON t3.business_id = t1.business_id JOIN neighbourhood AS t2 ON t2.business_id = t1.business_id WHERE t1.city = "Dallas" AND t3.category_name = "restaurant" AND t2.neighbourhood_name = "Hazelwood"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many Starbucks are there in Dallas Texas ? | SELECT COUNT ( DISTINCT business_id ) FROM business WHERE city = "Dallas" AND name = "Starbucks" AND state = "Texas"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many reviews does " Acacia Cafe " have ? | SELECT review_count FROM business WHERE name = "Acacia Cafe"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find the average number of checkins in restaurant " Barrio Cafe " per day | SELECT AVG ( t3.count ) , t3.day FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN checkin AS t3 ON t3.business_id = t1.business_id WHERE t1.name = "Barrio Cafe" AND t2.category_name = "restaurant" GROUP BY t3.day; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many businesses are there in the " Stone Meadows " neighbourhood in Madison ? | SELECT COUNT ( DISTINCT t1.name ) FROM neighbourhood AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.city = "Madison" AND t2.neighbourhood_name = "Stone Meadows"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many reviews has Adrienne written ? | SELECT COUNT ( DISTINCT t1.text ) FROM USER AS t2 JOIN review AS t1 ON t2.user_id = t1.user_id WHERE t2.name = "Adrienne"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many reviews has Michelle written in March 2014 ? | SELECT COUNT ( DISTINCT t1.text ) FROM USER AS t2 JOIN review AS t1 ON t2.user_id = t1.user_id WHERE t1.month = "March" AND t1.year = 2014 AND t2.name = "Michelle"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many businesses has Michelle reviewed in 2010 ? | SELECT COUNT ( DISTINCT t1.name ) FROM review AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN USER AS t3 ON t3.user_id = t2.user_id WHERE t2.year = 2010 AND t3.name = "Michelle"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many businesses in " San Diego " has Christine reviewed in 2010 ? | SELECT COUNT ( DISTINCT t1.name ) FROM review AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN USER AS t3 ON t3.user_id = t2.user_id WHERE t1.city = "San Diego" AND t2.year = 2010 AND t3.name = "Christine"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many Target are there in " Los Angeles " ? | SELECT COUNT ( DISTINCT business_id ) FROM business WHERE city = "Los Angeles" AND name = "Target"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many users have reviewed Irish Pub in Dallas ? | SELECT COUNT ( DISTINCT t4.name ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN review AS t3 ON t3.business_id = t1.business_id JOIN USER AS t4 ON t4.user_id = t3.user_id WHERE t1.city = "Dallas" AND t2.category_name = "Irish Pub"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | What is the average rating of reviews written in year 2014 ? | SELECT AVG ( rating ) FROM review WHERE YEAR = 2014; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many people reviewed restaurant " Vintner Grill " in 2010 ? | SELECT COUNT ( DISTINCT t4.name ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN review AS t3 ON t3.business_id = t1.business_id JOIN USER AS t4 ON t4.user_id = t3.user_id WHERE t1.name = "Vintner Grill" AND t2.category_name = "category_category_name0" AND t3.year = 2010; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find the number of reviews on businesses located in " South Summerlin " neighbourhood | SELECT COUNT ( DISTINCT t3.text ) FROM neighbourhood AS t1 JOIN business AS t2 ON t1.business_id = t2.business_id JOIN review AS t3 ON t3.business_id = t2.business_id WHERE t1.neighbourhood_name = "South Summerlin"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find the number of users called Michelle | SELECT COUNT ( DISTINCT name ) FROM USER WHERE name = "Michelle"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Return me the number of businesses that are restaurant . | SELECT COUNT ( DISTINCT t1.name ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t2.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Return me the number of cities that has " Panda Express " . | SELECT COUNT ( DISTINCT city ) FROM business WHERE name = "Panda Express"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Return me the number of tips that are written by Michelle . | SELECT COUNT ( DISTINCT t1.text ) FROM USER AS t2 JOIN tip AS t1 ON t2.user_id = t1.user_id WHERE t2.name = "Michelle"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find the total checkins in " Brighton Heights " neighbourhood | SELECT SUM ( t3.count ) FROM checkin AS t3 JOIN business AS t1 ON t3.business_id = t1.business_id JOIN neighbourhood AS t2 ON t2.business_id = t1.business_id WHERE t2.neighbourhood_name = "Brighton Heights"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find the total number of reviews written in March | SELECT COUNT ( DISTINCT text ) FROM review WHERE MONTH = "March"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find the number of tips written in each month | SELECT COUNT ( DISTINCT text ) , MONTH FROM tip GROUP BY MONTH; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many neighbourhoods have a business with rating 5 in Madison ? | SELECT COUNT ( DISTINCT t1.neighbourhood_name ) FROM neighbourhood AS t1 JOIN business AS t2 ON t1.business_id = t2.business_id WHERE t2.city = "Madison" AND t2.rating = 5; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Give me all the Moroccan restaurant in Texas | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN category AS t3 ON t3.business_id = t1.business_id WHERE t1.state = "Texas" AND t2.category_name = "Moroccan" AND t3.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | which business has the most number of checkins | SELECT t1.name FROM checkin AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id GROUP BY t1.name ORDER BY SUM ( t2.count ) DESC LIMIT 1; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | which neighbourhood has the most number of businesses in Madison | SELECT t1.neighbourhood_name FROM neighbourhood AS t1 JOIN business AS t2 ON t1.business_id = t2.business_id WHERE t2.city = "Madison" GROUP BY t1.neighbourhood_name ORDER BY COUNT ( DISTINCT t2.name ) DESC LIMIT 1; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all Mexican restaurant in Dallas with at least 3.5 stars | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN category AS t3 ON t3.business_id = t1.business_id WHERE t1.city = "Dallas" AND t1.rating > 3.5 AND t2.category_name = "Mexican" AND t3.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all Mexican restaurant in Dallas with a rating above 3.5 | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN category AS t3 ON t3.business_id = t1.business_id WHERE t1.city = "Dallas" AND t1.rating > 3.5 AND t2.category_name = "Mexican" AND t3.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all restaurant with Valet Service in Dallas Texas | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN category AS t3 ON t3.business_id = t1.business_id WHERE t1.city = "Dallas" AND t1.state = "Texas" AND t2.category_name = "Valet Service" AND t3.category_name = "restaurant"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all Italian restaurant in the Meadowood neighbourhood of Madison | SELECT t1.name FROM category AS t3 JOIN business AS t1 ON t3.business_id = t1.business_id JOIN category AS t4 ON t4.business_id = t1.business_id JOIN neighbourhood AS t2 ON t2.business_id = t1.business_id WHERE t1.city = "Madison" AND t3.category_name = "Italian" AND t4.category_name = "restaurant" AND t2.neighbourhood_name = "Meadowood"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | Find all Bars in " Los Angeles " with at least 30 reviews and average rating above 3 stars | SELECT t1.name FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id WHERE t1.city = "Los Angeles" AND t1.rating > 3 AND t1.review_count > 30 AND t2.category_name = "Bars"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
yelp | How many Egyptian restaurant are there in Edinburgh ? | SELECT COUNT ( DISTINCT t1.name ) FROM category AS t2 JOIN business AS t1 ON t2.business_id = t1.business_id JOIN category AS t3 ON t3.business_id = t1.business_id WHERE t1.city = "Edinburgh" AND t2.category_name = "restaurant" AND t3.category_name = "Egyptian"; | CREATE TABLE "business" (
"bid" int,
"business_id" text,
"name" text,
"full_address" text,
"city" text,
"latitude" text,
"longitude" text,
"review_count" int,
"is_open" int,
"rating" real,
"state" text,
primary key("bid")
)
3 rows from business table:
Empty DataFrame
Columns: [bid, business_id, name, full_address, city, latitude, longitude, review_count, is_open, rating, state]
Index: []
CREATE TABLE "category" (
"id" int,
"business_id" text,
"category_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from category table:
Empty DataFrame
Columns: [id, business_id, category_name]
Index: []
CREATE TABLE "user" (
"uid" int,
"user_id" text,
"name" text,
primary key("uid")
)
3 rows from user table:
Empty DataFrame
Columns: [uid, user_id, name]
Index: []
CREATE TABLE "checkin" (
"cid" int,
"business_id" text,
"count" int,
"day" text,
primary key("cid"),
foreign key("business_id") references `business`("business_id")
)
3 rows from checkin table:
Empty DataFrame
Columns: [cid, business_id, count, day]
Index: []
CREATE TABLE "neighbourhood" (
"id" int,
"business_id" text,
"neighbourhood_name" text,
primary key("id"),
foreign key("business_id") references `business`("business_id")
)
3 rows from neighbourhood table:
Empty DataFrame
Columns: [id, business_id, neighbourhood_name]
Index: []
CREATE TABLE "review" (
"rid" int,
"business_id" text,
"user_id" text,
"rating" real,
"text" text,
"year" int,
"month" text,
primary key("rid"),
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from review table:
Empty DataFrame
Columns: [rid, business_id, user_id, rating, text, year, month]
Index: []
CREATE TABLE "tip" (
"tip_id" int,
"business_id" text,
"text" text,
"user_id" text,
"likes" int,
"year" int,
"month" text,
primary key("tip_id")
foreign key("business_id") references `business`("business_id"),
foreign key("user_id") references `user`("user_id")
)
3 rows from tip table:
Empty DataFrame
Columns: [tip_id, business_id, text, user_id, likes, year, month]
Index: []
|
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