query stringlengths 18 577 | table_names list | tables list | answer stringlengths 45 443k | source stringlengths 139 60.7M | target stringlengths 19 480k |
|---|---|---|---|---|---|
SELECT count(*) FROM catalog_contents | [
"Catalog_Contents"
] | [
"{\"columns\":[\"catalog_entry_id\",\"catalog_level_number\",\"parent_entry_id\",\"previous_entry_id\",\"next_entry_id\",\"catalog_entry_name\",\"product_stock_number\",\"price_in_dollars\",\"price_in_euros\",\"price_in_pounds\",\"capacity\",\"length\",\"height\",\"width\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,1... | {"columns":["count(*)"],"index":[0],"data":[[15]]} | SELECT count(*) FROM catalog_contents <table_name> : Catalog_Contents col : catalog_entry_id | catalog_level_number | parent_entry_id | previous_entry_id | next_entry_id | catalog_entry_name | product_stock_number | price_in_dollars | price_in_euros | price_in_pounds | capacity | length | height | width row 1 : 1 | 1 |... | col : count(*) row 1 : 15 |
SELECT catalog_entry_name FROM catalog_contents WHERE next_entry_id > 8 | [
"Catalog_Contents"
] | [
"{\"columns\":[\"catalog_entry_id\",\"catalog_level_number\",\"parent_entry_id\",\"previous_entry_id\",\"next_entry_id\",\"catalog_entry_name\",\"product_stock_number\",\"price_in_dollars\",\"price_in_euros\",\"price_in_pounds\",\"capacity\",\"length\",\"height\",\"width\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,1... | {"columns":["catalog_entry_name"],"index":[0,1,2],"data":[["Sprite Lemo"],["Diet Pepsi"],["Wanglaoji"]]} | SELECT catalog_entry_name FROM catalog_contents WHERE next_entry_id > 8 <table_name> : Catalog_Contents col : catalog_entry_id | catalog_level_number | parent_entry_id | previous_entry_id | next_entry_id | catalog_entry_name | product_stock_number | price_in_dollars | price_in_euros | price_in_pounds | capacity | len... | col : catalog_entry_name row 1 : Sprite Lemo row 2 : Diet Pepsi row 3 : Wanglaoji |
SELECT count(*) FROM Aircraft | [
"aircraft"
] | [
"{\"columns\":[\"aid\",\"name\",\"distance\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],\"data\":[[1,\"Boeing 747-400\",8430],[2,\"Boeing 737-800\",3383],[3,\"Airbus A340-300\",7120],[4,\"British Aerospace Jetstream 41\",1502],[5,\"Embraer ERJ-145\",1530],[6,\"SAAB 340\",2128],[7,\"Piper Archer III\",520],[... | {"columns":["count(*)"],"index":[0],"data":[[16]]} | SELECT count(*) FROM Aircraft <table_name> : aircraft col : aid | name | distance row 1 : 1 | Boeing 747-400 | 8430 row 2 : 2 | Boeing 737-800 | 3383 row 3 : 3 | Airbus A340-300 | 7120 row 4 : 4 | British Aerospace Jetstream 41 | 1502 row 5 : 5 | Embraer ERJ-145 | 1530 row 6 : 6 | SAAB 340 | 2128 row 7 : 7 | Piper Arch... | col : count(*) row 1 : 16 |
SELECT name , distance FROM Aircraft | [
"aircraft"
] | [
"{\"columns\":[\"aid\",\"name\",\"distance\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],\"data\":[[1,\"Boeing 747-400\",8430],[2,\"Boeing 737-800\",3383],[3,\"Airbus A340-300\",7120],[4,\"British Aerospace Jetstream 41\",1502],[5,\"Embraer ERJ-145\",1530],[6,\"SAAB 340\",2128],[7,\"Piper Archer III\",520],[... | {"columns":["name","distance"],"index":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],"data":[["Boeing 747-400",8430],["Boeing 737-800",3383],["Airbus A340-300",7120],["British Aerospace Jetstream 41",1502],["Embraer ERJ-145",1530],["SAAB 340",2128],["Piper Archer III",520],["Tupolev 154",4103],["Schwitzer 2-33",30],["Lockhee... | SELECT name , distance FROM Aircraft <table_name> : aircraft col : aid | name | distance row 1 : 1 | Boeing 747-400 | 8430 row 2 : 2 | Boeing 737-800 | 3383 row 3 : 3 | Airbus A340-300 | 7120 row 4 : 4 | British Aerospace Jetstream 41 | 1502 row 5 : 5 | Embraer ERJ-145 | 1530 row 6 : 6 | SAAB 340 | 2128 row 7 : 7 | Pi... | col : name | distance row 1 : Boeing 747-400 | 8430 row 2 : Boeing 737-800 | 3383 row 3 : Airbus A340-300 | 7120 row 4 : British Aerospace Jetstream 41 | 1502 row 5 : Embraer ERJ-145 | 1530 row 6 : SAAB 340 | 2128 row 7 : Piper Archer III | 520 row 8 : Tupolev 154 | 4103 row 9 : Schwitzer 2-33 | 30 row 10 : Lockheed L1... |
SELECT aid FROM Aircraft WHERE distance > 1000 | [
"aircraft"
] | [
"{\"columns\":[\"aid\",\"name\",\"distance\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],\"data\":[[1,\"Boeing 747-400\",8430],[2,\"Boeing 737-800\",3383],[3,\"Airbus A340-300\",7120],[4,\"British Aerospace Jetstream 41\",1502],[5,\"Embraer ERJ-145\",1530],[6,\"SAAB 340\",2128],[7,\"Piper Archer III\",520],[... | {"columns":["aid"],"index":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],"data":[[1],[2],[3],[4],[5],[6],[8],[9],[10],[11],[12],[13],[14],[15]]} | SELECT aid FROM Aircraft WHERE distance > 1000 <table_name> : aircraft col : aid | name | distance row 1 : 1 | Boeing 747-400 | 8430 row 2 : 2 | Boeing 737-800 | 3383 row 3 : 3 | Airbus A340-300 | 7120 row 4 : 4 | British Aerospace Jetstream 41 | 1502 row 5 : 5 | Embraer ERJ-145 | 1530 row 6 : 6 | SAAB 340 | 2128 row... | col : aid row 1 : 1 row 2 : 2 row 3 : 3 row 4 : 4 row 5 : 5 row 6 : 6 row 7 : 8 row 8 : 9 row 9 : 10 row 10 : 11 row 11 : 12 row 12 : 13 row 13 : 14 row 14 : 15 |
SELECT count(*) FROM Aircraft WHERE distance BETWEEN 1000 AND 5000 | [
"aircraft"
] | [
"{\"columns\":[\"aid\",\"name\",\"distance\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],\"data\":[[1,\"Boeing 747-400\",8430],[2,\"Boeing 737-800\",3383],[3,\"Airbus A340-300\",7120],[4,\"British Aerospace Jetstream 41\",1502],[5,\"Embraer ERJ-145\",1530],[6,\"SAAB 340\",2128],[7,\"Piper Archer III\",520],[... | {"columns":["count(*)"],"index":[0],"data":[[9]]} | SELECT count(*) FROM Aircraft WHERE distance BETWEEN 1000 AND 5000 <table_name> : aircraft col : aid | name | distance row 1 : 1 | Boeing 747-400 | 8430 row 2 : 2 | Boeing 737-800 | 3383 row 3 : 3 | Airbus A340-300 | 7120 row 4 : 4 | British Aerospace Jetstream 41 | 1502 row 5 : 5 | Embraer ERJ-145 | 1530 row 6 : 6 | S... | col : count(*) row 1 : 9 |
SELECT name , distance FROM Aircraft WHERE aid = 12 | [
"aircraft"
] | [
"{\"columns\":[\"aid\",\"name\",\"distance\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],\"data\":[[1,\"Boeing 747-400\",8430],[2,\"Boeing 737-800\",3383],[3,\"Airbus A340-300\",7120],[4,\"British Aerospace Jetstream 41\",1502],[5,\"Embraer ERJ-145\",1530],[6,\"SAAB 340\",2128],[7,\"Piper Archer III\",520],[... | {"columns":["name","distance"],"index":[0],"data":[["Boeing 767-400ER",6475]]} | SELECT name , distance FROM Aircraft WHERE aid = 12 <table_name> : aircraft col : aid | name | distance row 1 : 1 | Boeing 747-400 | 8430 row 2 : 2 | Boeing 737-800 | 3383 row 3 : 3 | Airbus A340-300 | 7120 row 4 : 4 | British Aerospace Jetstream 41 | 1502 row 5 : 5 | Embraer ERJ-145 | 1530 row 6 : 6 | SAAB 340 | 21... | col : name | distance row 1 : Boeing 767-400ER | 6475 |
SELECT min(distance) , avg(distance) , max(distance) FROM Aircraft | [
"aircraft"
] | [
"{\"columns\":[\"aid\",\"name\",\"distance\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],\"data\":[[1,\"Boeing 747-400\",8430],[2,\"Boeing 737-800\",3383],[3,\"Airbus A340-300\",7120],[4,\"British Aerospace Jetstream 41\",1502],[5,\"Embraer ERJ-145\",1530],[6,\"SAAB 340\",2128],[7,\"Piper Archer III\",520],[... | {"columns":["min(distance)","avg(distance)","max(distance)"],"index":[0],"data":[[30,3655.375,8430]]} | SELECT min(distance) , avg(distance) , max(distance) FROM Aircraft <table_name> : aircraft col : aid | name | distance row 1 : 1 | Boeing 747-400 | 8430 row 2 : 2 | Boeing 737-800 | 3383 row 3 : 3 | Airbus A340-300 | 7120 row 4 : 4 | British Aerospace Jetstream 41 | 1502 row 5 : 5 | Embraer ERJ-145 | 1530 row 6 : 6 |... | col : min(distance) | avg(distance) | max(distance) row 1 : 30 | 3655.375 | 8430 |
SELECT aid , name FROM Aircraft ORDER BY distance DESC LIMIT 1 | [
"aircraft"
] | [
"{\"columns\":[\"aid\",\"name\",\"distance\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],\"data\":[[1,\"Boeing 747-400\",8430],[2,\"Boeing 737-800\",3383],[3,\"Airbus A340-300\",7120],[4,\"British Aerospace Jetstream 41\",1502],[5,\"Embraer ERJ-145\",1530],[6,\"SAAB 340\",2128],[7,\"Piper Archer III\",520],[... | {"columns":["aid","name"],"index":[0],"data":[[1,"Boeing 747-400"]]} | SELECT aid , name FROM Aircraft ORDER BY distance DESC LIMIT 1 <table_name> : aircraft col : aid | name | distance row 1 : 1 | Boeing 747-400 | 8430 row 2 : 2 | Boeing 737-800 | 3383 row 3 : 3 | Airbus A340-300 | 7120 row 4 : 4 | British Aerospace Jetstream 41 | 1502 row 5 : 5 | Embraer ERJ-145 | 1530 row 6 : 6 | SAAB... | col : aid | name row 1 : 1 | Boeing 747-400 |
SELECT name FROM Aircraft ORDER BY distance LIMIT 3 | [
"aircraft"
] | [
"{\"columns\":[\"aid\",\"name\",\"distance\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],\"data\":[[1,\"Boeing 747-400\",8430],[2,\"Boeing 737-800\",3383],[3,\"Airbus A340-300\",7120],[4,\"British Aerospace Jetstream 41\",1502],[5,\"Embraer ERJ-145\",1530],[6,\"SAAB 340\",2128],[7,\"Piper Archer III\",520],[... | {"columns":["name"],"index":[0,1,2],"data":[["Schwitzer 2-33"],["Piper Archer III"],["British Aerospace Jetstream 41"]]} | SELECT name FROM Aircraft ORDER BY distance LIMIT 3 <table_name> : aircraft col : aid | name | distance row 1 : 1 | Boeing 747-400 | 8430 row 2 : 2 | Boeing 737-800 | 3383 row 3 : 3 | Airbus A340-300 | 7120 row 4 : 4 | British Aerospace Jetstream 41 | 1502 row 5 : 5 | Embraer ERJ-145 | 1530 row 6 : 6 | SAAB 340 | 2128 ... | col : name row 1 : Schwitzer 2-33 row 2 : Piper Archer III row 3 : British Aerospace Jetstream 41 |
SELECT name FROM Aircraft WHERE distance > (SELECT avg(distance) FROM Aircraft) | [
"aircraft"
] | [
"{\"columns\":[\"aid\",\"name\",\"distance\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],\"data\":[[1,\"Boeing 747-400\",8430],[2,\"Boeing 737-800\",3383],[3,\"Airbus A340-300\",7120],[4,\"British Aerospace Jetstream 41\",1502],[5,\"Embraer ERJ-145\",1530],[6,\"SAAB 340\",2128],[7,\"Piper Archer III\",520],[... | {"columns":["name"],"index":[0,1,2,3,4,5,6],"data":[["Boeing 747-400"],["Airbus A340-300"],["Tupolev 154"],["Lockheed L1011"],["Boeing 757-300"],["Boeing 777-300"],["Boeing 767-400ER"]]} | SELECT name FROM Aircraft WHERE distance > (SELECT avg(distance) FROM Aircraft) <table_name> : aircraft col : aid | name | distance row 1 : 1 | Boeing 747-400 | 8430 row 2 : 2 | Boeing 737-800 | 3383 row 3 : 3 | Airbus A340-300 | 7120 row 4 : 4 | British Aerospace Jetstream 41 | 1502 row 5 : 5 | Embraer ERJ-145 | 153... | col : name row 1 : Boeing 747-400 row 2 : Airbus A340-300 row 3 : Tupolev 154 row 4 : Lockheed L1011 row 5 : Boeing 757-300 row 6 : Boeing 777-300 row 7 : Boeing 767-400ER |
SELECT count(*) FROM Employee | [
"employee"
] | [
"{\"columns\":[\"eid\",\"name\",\"salary\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30],\"data\":[[242518965,\"James Smith\",120433],[141582651,\"Mary Johnson\",178345],[11564812,\"John Williams\",153972],[567354612,\"Lisa Walker\",256481],[552455318,\"Larry West\"... | {"columns":["count(*)"],"index":[0],"data":[[31]]} | SELECT count(*) FROM Employee <table_name> : employee col : eid | name | salary row 1 : 242518965 | James Smith | 120433 row 2 : 141582651 | Mary Johnson | 178345 row 3 : 11564812 | John Williams | 153972 row 4 : 567354612 | Lisa Walker | 256481 row 5 : 552455318 | Larry West | 101745 row 6 : 550156548 | Karen Scott | ... | col : count(*) row 1 : 31 |
SELECT name , salary FROM Employee ORDER BY salary | [
"employee"
] | [
"{\"columns\":[\"eid\",\"name\",\"salary\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30],\"data\":[[242518965,\"James Smith\",120433],[141582651,\"Mary Johnson\",178345],[11564812,\"John Williams\",153972],[567354612,\"Lisa Walker\",256481],[552455318,\"Larry West\"... | {"columns":["name","salary"],"index":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30],"data":[["Milo Brooks",20],["Donald King",18050],["Richard Jackson",23980],["Patricia Jones",24450],["Linda Davis",27984],["Elizabeth Taylor",32021],["Haywood Kelly",32899],["Chad Stewart",33546],["... | SELECT name , salary FROM Employee ORDER BY salary <table_name> : employee col : eid | name | salary row 1 : 242518965 | James Smith | 120433 row 2 : 141582651 | Mary Johnson | 178345 row 3 : 11564812 | John Williams | 153972 row 4 : 567354612 | Lisa Walker | 256481 row 5 : 552455318 | Larry West | 101745 row 6 : 5501... | col : name | salary row 1 : Milo Brooks | 20 row 2 : Donald King | 18050 row 3 : Richard Jackson | 23980 row 4 : Patricia Jones | 24450 row 5 : Linda Davis | 27984 row 6 : Elizabeth Taylor | 32021 row 7 : Haywood Kelly | 32899 row 8 : Chad Stewart | 33546 row 9 : David Anderson | 43001 row 10 : Barbara Wilson | 43723 r... |
SELECT eid FROM Employee WHERE salary > 100000 | [
"employee"
] | [
"{\"columns\":[\"eid\",\"name\",\"salary\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30],\"data\":[[242518965,\"James Smith\",120433],[141582651,\"Mary Johnson\",178345],[11564812,\"John Williams\",153972],[567354612,\"Lisa Walker\",256481],[552455318,\"Larry West\"... | {"columns":["eid"],"index":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14],"data":[[242518965],[141582651],[11564812],[567354612],[552455318],[550156548],[390487451],[355548984],[310454876],[142519864],[269734834],[552455348],[556784565],[573284895],[574489456]]} | SELECT eid FROM Employee WHERE salary > 100000 <table_name> : employee col : eid | name | salary row 1 : 242518965 | James Smith | 120433 row 2 : 141582651 | Mary Johnson | 178345 row 3 : 11564812 | John Williams | 153972 row 4 : 567354612 | Lisa Walker | 256481 row 5 : 552455318 | Larry West | 101745 row 6 : 5501565... | col : eid row 1 : 242518965 row 2 : 141582651 row 3 : 11564812 row 4 : 567354612 row 5 : 552455318 row 6 : 550156548 row 7 : 390487451 row 8 : 355548984 row 9 : 310454876 row 10 : 142519864 row 11 : 269734834 row 12 : 552455348 row 13 : 556784565 row 14 : 573284895 row 15 : 574489456 |
SELECT count(*) FROM Employee WHERE salary BETWEEN 100000 AND 200000 | [
"employee"
] | [
"{\"columns\":[\"eid\",\"name\",\"salary\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30],\"data\":[[242518965,\"James Smith\",120433],[141582651,\"Mary Johnson\",178345],[11564812,\"John Williams\",153972],[567354612,\"Lisa Walker\",256481],[552455318,\"Larry West\"... | {"columns":["count(*)"],"index":[0],"data":[[7]]} | SELECT count(*) FROM Employee WHERE salary BETWEEN 100000 AND 200000 <table_name> : employee col : eid | name | salary row 1 : 242518965 | James Smith | 120433 row 2 : 141582651 | Mary Johnson | 178345 row 3 : 11564812 | John Williams | 153972 row 4 : 567354612 | Lisa Walker | 256481 row 5 : 552455318 | Larry West | 10... | col : count(*) row 1 : 7 |
SELECT name , salary FROM Employee WHERE eid = 242518965 | [
"employee"
] | [
"{\"columns\":[\"eid\",\"name\",\"salary\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30],\"data\":[[242518965,\"James Smith\",120433],[141582651,\"Mary Johnson\",178345],[11564812,\"John Williams\",153972],[567354612,\"Lisa Walker\",256481],[552455318,\"Larry West\"... | {"columns":["name","salary"],"index":[0],"data":[["James Smith",120433]]} | SELECT name , salary FROM Employee WHERE eid = 242518965 <table_name> : employee col : eid | name | salary row 1 : 242518965 | James Smith | 120433 row 2 : 141582651 | Mary Johnson | 178345 row 3 : 11564812 | John Williams | 153972 row 4 : 567354612 | Lisa Walker | 256481 row 5 : 552455318 | Larry West | 101745 row ... | col : name | salary row 1 : James Smith | 120433 |
SELECT avg(salary) , max(salary) FROM Employee | [
"employee"
] | [
"{\"columns\":[\"eid\",\"name\",\"salary\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30],\"data\":[[242518965,\"James Smith\",120433],[141582651,\"Mary Johnson\",178345],[11564812,\"John Williams\",153972],[567354612,\"Lisa Walker\",256481],[552455318,\"Larry West\"... | {"columns":["avg(salary)","max(salary)"],"index":[0],"data":[[109915.3870967742,289950]]} | SELECT avg(salary) , max(salary) FROM Employee <table_name> : employee col : eid | name | salary row 1 : 242518965 | James Smith | 120433 row 2 : 141582651 | Mary Johnson | 178345 row 3 : 11564812 | John Williams | 153972 row 4 : 567354612 | Lisa Walker | 256481 row 5 : 552455318 | Larry West | 101745 row 6 : 55015654... | col : avg(salary) | max(salary) row 1 : 109915.3870967742 | 289950 |
SELECT eid , name FROM Employee ORDER BY salary DESC LIMIT 1 | [
"employee"
] | [
"{\"columns\":[\"eid\",\"name\",\"salary\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30],\"data\":[[242518965,\"James Smith\",120433],[141582651,\"Mary Johnson\",178345],[11564812,\"John Williams\",153972],[567354612,\"Lisa Walker\",256481],[552455318,\"Larry West\"... | {"columns":["eid","name"],"index":[0],"data":[[269734834,"George Wright"]]} | SELECT eid , name FROM Employee ORDER BY salary DESC LIMIT 1 <table_name> : employee col : eid | name | salary row 1 : 242518965 | James Smith | 120433 row 2 : 141582651 | Mary Johnson | 178345 row 3 : 11564812 | John Williams | 153972 row 4 : 567354612 | Lisa Walker | 256481 row 5 : 552455318 | Larry West | 101745 ro... | col : eid | name row 1 : 269734834 | George Wright |
SELECT name FROM Employee ORDER BY salary ASC LIMIT 3 | [
"employee"
] | [
"{\"columns\":[\"eid\",\"name\",\"salary\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30],\"data\":[[242518965,\"James Smith\",120433],[141582651,\"Mary Johnson\",178345],[11564812,\"John Williams\",153972],[567354612,\"Lisa Walker\",256481],[552455318,\"Larry West\"... | {"columns":["name"],"index":[0,1,2],"data":[["Milo Brooks"],["Donald King"],["Richard Jackson"]]} | SELECT name FROM Employee ORDER BY salary ASC LIMIT 3 <table_name> : employee col : eid | name | salary row 1 : 242518965 | James Smith | 120433 row 2 : 141582651 | Mary Johnson | 178345 row 3 : 11564812 | John Williams | 153972 row 4 : 567354612 | Lisa Walker | 256481 row 5 : 552455318 | Larry West | 101745 row 6 : 55... | col : name row 1 : Milo Brooks row 2 : Donald King row 3 : Richard Jackson |
SELECT name FROM Employee WHERE salary > (SELECT avg(salary) FROM Employee) | [
"employee"
] | [
"{\"columns\":[\"eid\",\"name\",\"salary\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30],\"data\":[[242518965,\"James Smith\",120433],[141582651,\"Mary Johnson\",178345],[11564812,\"John Williams\",153972],[567354612,\"Lisa Walker\",256481],[552455318,\"Larry West\"... | {"columns":["name"],"index":[0,1,2,3,4,5,6,7,8,9,10,11,12],"data":[["James Smith"],["Mary Johnson"],["John Williams"],["Lisa Walker"],["Karen Scott"],["Lawrence Sperry"],["Angela Martinez"],["Joseph Thompson"],["Betty Adams"],["George Wright"],["Dorthy Lewis"],["Mark Young"],["Eric Cooper"]]} | SELECT name FROM Employee WHERE salary > (SELECT avg(salary) FROM Employee) <table_name> : employee col : eid | name | salary row 1 : 242518965 | James Smith | 120433 row 2 : 141582651 | Mary Johnson | 178345 row 3 : 11564812 | John Williams | 153972 row 4 : 567354612 | Lisa Walker | 256481 row 5 : 552455318 | Larry ... | col : name row 1 : James Smith row 2 : Mary Johnson row 3 : John Williams row 4 : Lisa Walker row 5 : Karen Scott row 6 : Lawrence Sperry row 7 : Angela Martinez row 8 : Joseph Thompson row 9 : Betty Adams row 10 : George Wright row 11 : Dorthy Lewis row 12 : Mark Young row 13 : Eric Cooper |
SELECT eid , salary FROM Employee WHERE name = 'Mark Young' | [
"employee"
] | [
"{\"columns\":[\"eid\",\"name\",\"salary\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30],\"data\":[[242518965,\"James Smith\",120433],[141582651,\"Mary Johnson\",178345],[11564812,\"John Williams\",153972],[567354612,\"Lisa Walker\",256481],[552455318,\"Larry West\"... | {"columns":["eid","salary"],"index":[0],"data":[[556784565,205187]]} | SELECT eid , salary FROM Employee WHERE name = 'Mark Young' <table_name> : employee col : eid | name | salary row 1 : 242518965 | James Smith | 120433 row 2 : 141582651 | Mary Johnson | 178345 row 3 : 11564812 | John Williams | 153972 row 4 : 567354612 | Lisa Walker | 256481 row 5 : 552455318 | Larry West | 101745 r... | col : eid | salary row 1 : 556784565 | 205187 |
SELECT count(*) FROM Flight | [
"flight"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["count(*)"],"index":[0],"data":[[10]]} | SELECT count(*) FROM Flight <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.98 | 1 row 2 : 13 | Los Angeles | Chicago | 1749 | 04/12/2005 08:45 | 04/12/2005 08:4... | col : count(*) row 1 : 10 |
SELECT flno , origin , destination FROM Flight ORDER BY origin | [
"flight"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["flno","origin","destination"],"index":[0,1,2,3,4,5,6,7,8,9],"data":[[76,"Chicago","Los Angeles"],[68,"Chicago","New York"],[99,"Los Angeles","Washington D.C."],[13,"Los Angeles","Chicago"],[346,"Los Angeles","Dallas"],[387,"Los Angeles","Boston"],[7,"Los Angeles","Sydney"],[2,"Los Angeles","Tokyo"],[33,"Lo... | SELECT flno , origin , destination FROM Flight ORDER BY origin <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.98 | 1 row 2 : 13 | Los Angeles | Chicago | 1749... | col : flno | origin | destination row 1 : 76 | Chicago | Los Angeles row 2 : 68 | Chicago | New York row 3 : 99 | Los Angeles | Washington D.C. row 4 : 13 | Los Angeles | Chicago row 5 : 346 | Los Angeles | Dallas row 6 : 387 | Los Angeles | Boston row 7 : 7 | Los Angeles | Sydney row 8 : 2 | Los Angeles | Tokyo row 9 ... |
SELECT flno FROM Flight WHERE origin = "Los Angeles" | [
"flight"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["flno"],"index":[0,1,2,3,4,5,6,7],"data":[[99],[13],[346],[387],[7],[2],[33],[34]]} | SELECT flno FROM Flight WHERE origin = "Los Angeles" <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.98 | 1 row 2 : 13 | Los Angeles | Chicago | 1749 | 04/12/2... | col : flno row 1 : 99 row 2 : 13 row 3 : 346 row 4 : 387 row 5 : 7 row 6 : 2 row 7 : 33 row 8 : 34 |
SELECT origin FROM Flight WHERE destination = "Honolulu" | [
"flight"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["origin"],"index":[0,1],"data":[["Los Angeles"],["Los Angeles"]]} | SELECT origin FROM Flight WHERE destination = "Honolulu" <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.98 | 1 row 2 : 13 | Los Angeles | Chicago | 1749 | 04/... | col : origin row 1 : Los Angeles row 2 : Los Angeles |
SELECT departure_date , arrival_date FROM Flight WHERE origin = "Los Angeles" AND destination = "Honolulu" | [
"flight"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["departure_date","arrival_date"],"index":[0,1],"data":[["04\/12\/2005 09:15","04\/12\/2005 11:15"],["04\/12\/2005 12:45","04\/12\/2005 03:18"]]} | SELECT departure_date , arrival_date FROM Flight WHERE origin = "Los Angeles" AND destination = "Honolulu" <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.9... | col : departure_date | arrival_date row 1 : 04/12/2005 09:15 | 04/12/2005 11:15 row 2 : 04/12/2005 12:45 | 04/12/2005 03:18 |
SELECT flno FROM Flight WHERE distance > 2000 | [
"flight"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["flno"],"index":[0,1,2,3,4,5],"data":[[99],[387],[7],[2],[33],[34]]} | SELECT flno FROM Flight WHERE distance > 2000 <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.98 | 1 row 2 : 13 | Los Angeles | Chicago | 1749 | 04/12/2005 08:... | col : flno row 1 : 99 row 2 : 387 row 3 : 7 row 4 : 2 row 5 : 33 row 6 : 34 |
SELECT avg(price) FROM Flight WHERE origin = "Los Angeles" AND destination = "Honolulu" | [
"flight"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["avg(price)"],"index":[0],"data":[[400.605]]} | SELECT avg(price) FROM Flight WHERE origin = "Los Angeles" AND destination = "Honolulu" <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.98 | 1 row 2 : 13 | L... | col : avg(price) row 1 : 400.605 |
SELECT origin , destination FROM Flight WHERE price > 300 | [
"flight"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["origin","destination"],"index":[0,1,2],"data":[["Los Angeles","Tokyo"],["Los Angeles","Honolulu"],["Los Angeles","Honolulu"]]} | SELECT origin , destination FROM Flight WHERE price > 300 <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.98 | 1 row 2 : 13 | Los Angeles | Chicago | 1749 | 0... | col : origin | destination row 1 : Los Angeles | Tokyo row 2 : Los Angeles | Honolulu row 3 : Los Angeles | Honolulu |
SELECT flno , distance FROM Flight ORDER BY price DESC LIMIT 1 | [
"flight"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["flno","distance"],"index":[0],"data":[[2,5478]]} | SELECT flno , distance FROM Flight ORDER BY price DESC LIMIT 1 <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.98 | 1 row 2 : 13 | Los Angeles | Chicago | 1749 ... | col : flno | distance row 1 : 2 | 5478 |
SELECT flno FROM Flight ORDER BY distance ASC LIMIT 3 | [
"flight"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["flno"],"index":[0,1,2],"data":[[68],[346],[13]]} | SELECT flno FROM Flight ORDER BY distance ASC LIMIT 3 <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.98 | 1 row 2 : 13 | Los Angeles | Chicago | 1749 | 04/12/20... | col : flno row 1 : 68 row 2 : 346 row 3 : 13 |
SELECT avg(distance) , avg(price) FROM Flight WHERE origin = "Los Angeles" | [
"flight"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["avg(distance)","avg(price)"],"index":[0],"data":[[3247.625,345.16]]} | SELECT avg(distance) , avg(price) FROM Flight WHERE origin = "Los Angeles" <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.98 | 1 row 2 : 13 | Los Angeles | C... | col : avg(distance) | avg(price) row 1 : 3247.625 | 345.16 |
SELECT origin , count(*) FROM Flight GROUP BY origin | [
"flight"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["origin","count(*)"],"index":[0,1],"data":[["Chicago",2],["Los Angeles",8]]} | SELECT origin , count(*) FROM Flight GROUP BY origin <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.98 | 1 row 2 : 13 | Los Angeles | Chicago | 1749 | 04/12/20... | col : origin | count(*) row 1 : Chicago | 2 row 2 : Los Angeles | 8 |
SELECT destination , count(*) FROM Flight GROUP BY destination | [
"flight"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["destination","count(*)"],"index":[0,1,2,3,4,5,6,7,8],"data":[["Boston",1],["Chicago",1],["Dallas",1],["Honolulu",2],["Los Angeles",1],["New York",1],["Sydney",1],["Tokyo",1],["Washington D.C.",1]]} | SELECT destination , count(*) FROM Flight GROUP BY destination <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.98 | 1 row 2 : 13 | Los Angeles | Chicago | 1749 ... | col : destination | count(*) row 1 : Boston | 1 row 2 : Chicago | 1 row 3 : Dallas | 1 row 4 : Honolulu | 2 row 5 : Los Angeles | 1 row 6 : New York | 1 row 7 : Sydney | 1 row 8 : Tokyo | 1 row 9 : Washington D.C. | 1 |
SELECT origin FROM Flight GROUP BY origin ORDER BY count(*) DESC LIMIT 1 | [
"flight"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["origin"],"index":[0],"data":[["Los Angeles"]]} | SELECT origin FROM Flight GROUP BY origin ORDER BY count(*) DESC LIMIT 1 <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.98 | 1 row 2 : 13 | Los Angeles | Chicag... | col : origin row 1 : Los Angeles |
SELECT destination FROM Flight GROUP BY destination ORDER BY count(*) LIMIT 1 | [
"flight"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["destination"],"index":[0],"data":[["Boston"]]} | SELECT destination FROM Flight GROUP BY destination ORDER BY count(*) LIMIT 1 <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.98 | 1 row 2 : 13 | Los Angeles | C... | col : destination row 1 : Boston |
SELECT T2.name FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid WHERE T1.flno = 99 | [
"flight",
"aircraft"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["name"],"index":[0],"data":[["Boeing 747-400"]]} | SELECT T2.name FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid WHERE T1.flno = 99 <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.98 | 1 row 2 : 13 ... | col : name row 1 : Boeing 747-400 |
SELECT T1.flno FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid WHERE T2.name = "Airbus A340-300" | [
"flight",
"aircraft"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["flno"],"index":[0,1],"data":[[13],[7]]} | SELECT T1.flno FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid WHERE T2.name = "Airbus A340-300" <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.98 ... | col : flno row 1 : 13 row 2 : 7 |
SELECT T2.name , count(*) FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid GROUP BY T1.aid | [
"flight",
"aircraft"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["name","count(*)"],"index":[0,1,2,3,4,5,6,7],"data":[["Boeing 747-400",1],["Boeing 737-800",1],["Airbus A340-300",2],["Embraer ERJ-145",1],["SAAB 340",1],["Piper Archer III",1],["Lockheed L1011",2],["Boeing 757-300",1]]} | SELECT T2.name , count(*) FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid GROUP BY T1.aid <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.98 | 1 row ... | col : name | count(*) row 1 : Boeing 747-400 | 1 row 2 : Boeing 737-800 | 1 row 3 : Airbus A340-300 | 2 row 4 : Embraer ERJ-145 | 1 row 5 : SAAB 340 | 1 row 6 : Piper Archer III | 1 row 7 : Lockheed L1011 | 2 row 8 : Boeing 757-300 | 1 |
SELECT T2.name FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid GROUP BY T1.aid HAVING count(*) >= 2 | [
"flight",
"aircraft"
] | [
"{\"columns\":[\"flno\",\"origin\",\"destination\",\"distance\",\"departure_date\",\"arrival_date\",\"price\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9],\"data\":[[99,\"Los Angeles\",\"Washington D.C.\",2308,\"04\\/12\\/2005 09:30\",\"04\\/12\\/2005 09:40\",235.98,1],[13,\"Los Angeles\",\"Chicago\",1749,\"04\\/12\\/2... | {"columns":["name"],"index":[0,1],"data":[["Airbus A340-300"],["Lockheed L1011"]]} | SELECT T2.name FROM Flight AS T1 JOIN Aircraft AS T2 ON T1.aid = T2.aid GROUP BY T1.aid HAVING count(*) >= 2 <table_name> : flight col : flno | origin | destination | distance | departure_date | arrival_date | price | aid row 1 : 99 | Los Angeles | Washington D.C. | 2308 | 04/12/2005 09:30 | 04/12/2005 09:40 | 235.9... | col : name row 1 : Airbus A340-300 row 2 : Lockheed L1011 |
SELECT count(DISTINCT eid) FROM Certificate | [
"certificate"
] | [
"{\"columns\":[\"eid\",\"aid\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68],\"data\":[[11564812,2],[11564812,10],[90873519,6],[141582651,2],[141582651,... | {"columns":["count(DISTINCT eid)"],"index":[0],"data":[[20]]} | SELECT count(DISTINCT eid) FROM Certificate <table_name> : certificate col : eid | aid row 1 : 11564812 | 2 row 2 : 11564812 | 10 row 3 : 90873519 | 6 row 4 : 141582651 | 2 row 5 : 141582651 | 10 row 6 : 141582651 | 12 row 7 : 142519864 | 1 row 8 : 142519864 | 2 row 9 : 142519864 | 3 row 10 : 142519864 | 7 row 11 : 142... | col : count(DISTINCT eid) row 1 : 20 |
SELECT eid FROM Employee EXCEPT SELECT eid FROM Certificate | [
"employee",
"certificate"
] | [
"{\"columns\":[\"eid\",\"name\",\"salary\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30],\"data\":[[242518965,\"James Smith\",120433],[141582651,\"Mary Johnson\",178345],[11564812,\"John Williams\",153972],[567354612,\"Lisa Walker\",256481],[552455318,\"Larry West\"... | {"columns":["eid"],"index":[0,1,2,3,4,5,6,7,8,9,10],"data":[[15645489],[248965255],[254099823],[287321212],[310454877],[348121549],[486512566],[489221823],[489456522],[552455348],[619023588]]} | SELECT eid FROM Employee EXCEPT SELECT eid FROM Certificate <table_name> : employee col : eid | name | salary row 1 : 242518965 | James Smith | 120433 row 2 : 141582651 | Mary Johnson | 178345 row 3 : 11564812 | John Williams | 153972 row 4 : 567354612 | Lisa Walker | 256481 row 5 : 552455318 | Larry West | 101745 row ... | col : eid row 1 : 15645489 row 2 : 248965255 row 3 : 254099823 row 4 : 287321212 row 5 : 310454877 row 6 : 348121549 row 7 : 486512566 row 8 : 489221823 row 9 : 489456522 row 10 : 552455348 row 11 : 619023588 |
SELECT T3.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T1.name = "John Williams" | [
"aircraft",
"employee",
"certificate"
] | [
"{\"columns\":[\"aid\",\"name\",\"distance\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],\"data\":[[1,\"Boeing 747-400\",8430],[2,\"Boeing 737-800\",3383],[3,\"Airbus A340-300\",7120],[4,\"British Aerospace Jetstream 41\",1502],[5,\"Embraer ERJ-145\",1530],[6,\"SAAB 340\",2128],[7,\"Piper Archer III\",520],[... | {"columns":["name"],"index":[0,1],"data":[["Boeing 737-800"],["Boeing 757-300"]]} | SELECT T3.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T1.name = "John Williams" <table_name> : aircraft col : aid | name | distance row 1 : 1 | Boeing 747-400 | 8430 row 2 : 2 | Boeing 737-800 | 3383 row 3 : 3 | Airbus A340-300 | 7120 row 4 : 4 |... | col : name row 1 : Boeing 737-800 row 2 : Boeing 757-300 |
SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = "Boeing 737-800" | [
"aircraft",
"employee",
"certificate"
] | [
"{\"columns\":[\"aid\",\"name\",\"distance\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],\"data\":[[1,\"Boeing 747-400\",8430],[2,\"Boeing 737-800\",3383],[3,\"Airbus A340-300\",7120],[4,\"British Aerospace Jetstream 41\",1502],[5,\"Embraer ERJ-145\",1530],[6,\"SAAB 340\",2128],[7,\"Piper Archer III\",520],[... | {"columns":["name"],"index":[0,1,2,3,4,5,6,7],"data":[["John Williams"],["Mary Johnson"],["Betty Adams"],["James Smith"],["George Wright"],["Larry West"],["Mark Young"],["Lisa Walker"]]} | SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = "Boeing 737-800" <table_name> : aircraft col : aid | name | distance row 1 : 1 | Boeing 747-400 | 8430 row 2 : 2 | Boeing 737-800 | 3383 row 3 : 3 | Airbus A340-300 | 7120 row 4 : 4 ... | col : name row 1 : John Williams row 2 : Mary Johnson row 3 : Betty Adams row 4 : James Smith row 5 : George Wright row 6 : Larry West row 7 : Mark Young row 8 : Lisa Walker |
SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = "Boeing 737-800" INTERSECT SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = "Airbus A340-300" | [
"aircraft",
"employee",
"certificate"
] | [
"{\"columns\":[\"aid\",\"name\",\"distance\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],\"data\":[[1,\"Boeing 747-400\",8430],[2,\"Boeing 737-800\",3383],[3,\"Airbus A340-300\",7120],[4,\"British Aerospace Jetstream 41\",1502],[5,\"Embraer ERJ-145\",1530],[6,\"SAAB 340\",2128],[7,\"Piper Archer III\",520],[... | {"columns":["name"],"index":[0,1,2,3],"data":[["Betty Adams"],["George Wright"],["Lisa Walker"],["Mark Young"]]} | SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = "Boeing 737-800" INTERSECT SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = "Airbus A340-300"... | col : name row 1 : Betty Adams row 2 : George Wright row 3 : Lisa Walker row 4 : Mark Young |
SELECT name FROM Employee EXCEPT SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = "Boeing 737-800" | [
"aircraft",
"employee",
"certificate"
] | [
"{\"columns\":[\"aid\",\"name\",\"distance\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],\"data\":[[1,\"Boeing 747-400\",8430],[2,\"Boeing 737-800\",3383],[3,\"Airbus A340-300\",7120],[4,\"British Aerospace Jetstream 41\",1502],[5,\"Embraer ERJ-145\",1530],[6,\"SAAB 340\",2128],[7,\"Piper Archer III\",520],[... | {"columns":["name"],"index":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21],"data":[["Angela Martinez"],["Barbara Wilson"],["Chad Stewart"],["David Anderson"],["Donald King"],["Dorthy Lewis"],["Elizabeth Taylor"],["Eric Cooper"],["Haywood Kelly"],["Jennifer Thomas"],["Joseph Thompson"],["Karen Scott"],["Lawre... | SELECT name FROM Employee EXCEPT SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.name = "Boeing 737-800" <table_name> : aircraft col : aid | name | distance row 1 : 1 | Boeing 747-400 | 8430 row 2 : 2 | Boeing 737-800 | 3383 row 3 : 3 | ... | col : name row 1 : Angela Martinez row 2 : Barbara Wilson row 3 : Chad Stewart row 4 : David Anderson row 5 : Donald King row 6 : Dorthy Lewis row 7 : Elizabeth Taylor row 8 : Eric Cooper row 9 : Haywood Kelly row 10 : Jennifer Thomas row 11 : Joseph Thompson row 12 : Karen Scott row 13 : Lawrence Sperry row 14 : Linda... |
SELECT T2.name FROM Certificate AS T1 JOIN Aircraft AS T2 ON T2.aid = T1.aid GROUP BY T1.aid ORDER BY count(*) DESC LIMIT 1 | [
"aircraft",
"certificate"
] | [
"{\"columns\":[\"aid\",\"name\",\"distance\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],\"data\":[[1,\"Boeing 747-400\",8430],[2,\"Boeing 737-800\",3383],[3,\"Airbus A340-300\",7120],[4,\"British Aerospace Jetstream 41\",1502],[5,\"Embraer ERJ-145\",1530],[6,\"SAAB 340\",2128],[7,\"Piper Archer III\",520],[... | {"columns":["name"],"index":[0],"data":[["Boeing 737-800"]]} | SELECT T2.name FROM Certificate AS T1 JOIN Aircraft AS T2 ON T2.aid = T1.aid GROUP BY T1.aid ORDER BY count(*) DESC LIMIT 1 <table_name> : aircraft col : aid | name | distance row 1 : 1 | Boeing 747-400 | 8430 row 2 : 2 | Boeing 737-800 | 3383 row 3 : 3 | Airbus A340-300 | 7120 row 4 : 4 | British Aerospace Jetstream... | col : name row 1 : Boeing 737-800 |
SELECT T2.name FROM Certificate AS T1 JOIN Aircraft AS T2 ON T2.aid = T1.aid WHERE T2.distance > 5000 GROUP BY T1.aid ORDER BY count(*) >= 5 | [
"aircraft",
"certificate"
] | [
"{\"columns\":[\"aid\",\"name\",\"distance\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],\"data\":[[1,\"Boeing 747-400\",8430],[2,\"Boeing 737-800\",3383],[3,\"Airbus A340-300\",7120],[4,\"British Aerospace Jetstream 41\",1502],[5,\"Embraer ERJ-145\",1530],[6,\"SAAB 340\",2128],[7,\"Piper Archer III\",520],[... | {"columns":["name"],"index":[0,1,2,3,4],"data":[["Boeing 747-400"],["Lockheed L1011"],["Boeing 777-300"],["Airbus A340-300"],["Boeing 767-400ER"]]} | SELECT T2.name FROM Certificate AS T1 JOIN Aircraft AS T2 ON T2.aid = T1.aid WHERE T2.distance > 5000 GROUP BY T1.aid ORDER BY count(*) >= 5 <table_name> : aircraft col : aid | name | distance row 1 : 1 | Boeing 747-400 | 8430 row 2 : 2 | Boeing 737-800 | 3383 row 3 : 3 | Airbus A340-300 | 7120 row 4 : 4 | Britis... | col : name row 1 : Boeing 747-400 row 2 : Lockheed L1011 row 3 : Boeing 777-300 row 4 : Airbus A340-300 row 5 : Boeing 767-400ER |
SELECT T1.name , T1.salary FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid GROUP BY T1.eid ORDER BY count(*) DESC LIMIT 1 | [
"employee",
"certificate"
] | [
"{\"columns\":[\"eid\",\"name\",\"salary\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30],\"data\":[[242518965,\"James Smith\",120433],[141582651,\"Mary Johnson\",178345],[11564812,\"John Williams\",153972],[567354612,\"Lisa Walker\",256481],[552455318,\"Larry West\"... | {"columns":["name","salary"],"index":[0],"data":[["George Wright",289950]]} | SELECT T1.name , T1.salary FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid GROUP BY T1.eid ORDER BY count(*) DESC LIMIT 1 <table_name> : employee col : eid | name | salary row 1 : 242518965 | James Smith | 120433 row 2 : 141582651 | Mary Johnson | 178345 row 3 : 11564812 | John Williams | 153972 row 4 ... | col : name | salary row 1 : George Wright | 289950 |
SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.distance > 5000 GROUP BY T1.eid ORDER BY count(*) DESC LIMIT 1 | [
"aircraft",
"employee",
"certificate"
] | [
"{\"columns\":[\"aid\",\"name\",\"distance\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15],\"data\":[[1,\"Boeing 747-400\",8430],[2,\"Boeing 737-800\",3383],[3,\"Airbus A340-300\",7120],[4,\"British Aerospace Jetstream 41\",1502],[5,\"Embraer ERJ-145\",1530],[6,\"SAAB 340\",2128],[7,\"Piper Archer III\",520],[... | {"columns":["name"],"index":[0],"data":[["George Wright"]]} | SELECT T1.name FROM Employee AS T1 JOIN Certificate AS T2 ON T1.eid = T2.eid JOIN Aircraft AS T3 ON T3.aid = T2.aid WHERE T3.distance > 5000 GROUP BY T1.eid ORDER BY count(*) DESC LIMIT 1 <table_name> : aircraft col : aid | name | distance row 1 : 1 | Boeing 747-400 | 8430 row 2 : 2 | Boeing 737-800 | 3383 row 3 ... | col : name row 1 : George Wright |
SELECT count(DISTINCT allergy) FROM Allergy_type | [
"Allergy_Type"
] | [
"{\"columns\":[\"Allergy\",\"AllergyType\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[\"Eggs\",\"food\"],[\"Nuts\",\"food\"],[\"Milk\",\"food\"],[\"Shellfish\",\"food\"],[\"Anchovies\",\"food\"],[\"Wheat\",\"food\"],[\"Soy\",\"food\"],[\"Ragweed\",\"environmental\"],[\"Tree Pollen\",\"environmental\"],... | {"columns":["count(DISTINCT allergy)"],"index":[0],"data":[[14]]} | SELECT count(DISTINCT allergy) FROM Allergy_type <table_name> : Allergy_Type col : Allergy | AllergyType row 1 : Eggs | food row 2 : Nuts | food row 3 : Milk | food row 4 : Shellfish | food row 5 : Anchovies | food row 6 : Wheat | food row 7 : Soy | food row 8 : Ragweed | environmental row 9 : Tree Pollen | environment... | col : count(DISTINCT allergy) row 1 : 14 |
SELECT count(DISTINCT allergytype) FROM Allergy_type | [
"Allergy_Type"
] | [
"{\"columns\":[\"Allergy\",\"AllergyType\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[\"Eggs\",\"food\"],[\"Nuts\",\"food\"],[\"Milk\",\"food\"],[\"Shellfish\",\"food\"],[\"Anchovies\",\"food\"],[\"Wheat\",\"food\"],[\"Soy\",\"food\"],[\"Ragweed\",\"environmental\"],[\"Tree Pollen\",\"environmental\"],... | {"columns":["count(DISTINCT allergytype)"],"index":[0],"data":[[3]]} | SELECT count(DISTINCT allergytype) FROM Allergy_type <table_name> : Allergy_Type col : Allergy | AllergyType row 1 : Eggs | food row 2 : Nuts | food row 3 : Milk | food row 4 : Shellfish | food row 5 : Anchovies | food row 6 : Wheat | food row 7 : Soy | food row 8 : Ragweed | environmental row 9 : Tree Pollen | environ... | col : count(DISTINCT allergytype) row 1 : 3 |
SELECT DISTINCT allergytype FROM Allergy_type | [
"Allergy_Type"
] | [
"{\"columns\":[\"Allergy\",\"AllergyType\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[\"Eggs\",\"food\"],[\"Nuts\",\"food\"],[\"Milk\",\"food\"],[\"Shellfish\",\"food\"],[\"Anchovies\",\"food\"],[\"Wheat\",\"food\"],[\"Soy\",\"food\"],[\"Ragweed\",\"environmental\"],[\"Tree Pollen\",\"environmental\"],... | {"columns":["AllergyType"],"index":[0,1,2],"data":[["food"],["environmental"],["animal"]]} | SELECT DISTINCT allergytype FROM Allergy_type <table_name> : Allergy_Type col : Allergy | AllergyType row 1 : Eggs | food row 2 : Nuts | food row 3 : Milk | food row 4 : Shellfish | food row 5 : Anchovies | food row 6 : Wheat | food row 7 : Soy | food row 8 : Ragweed | environmental row 9 : Tree Pollen | environmental ... | col : AllergyType row 1 : food row 2 : environmental row 3 : animal |
SELECT allergy , allergytype FROM Allergy_type | [
"Allergy_Type"
] | [
"{\"columns\":[\"Allergy\",\"AllergyType\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[\"Eggs\",\"food\"],[\"Nuts\",\"food\"],[\"Milk\",\"food\"],[\"Shellfish\",\"food\"],[\"Anchovies\",\"food\"],[\"Wheat\",\"food\"],[\"Soy\",\"food\"],[\"Ragweed\",\"environmental\"],[\"Tree Pollen\",\"environmental\"],... | {"columns":["Allergy","AllergyType"],"index":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],"data":[["Eggs","food"],["Nuts","food"],["Milk","food"],["Shellfish","food"],["Anchovies","food"],["Wheat","food"],["Soy","food"],["Ragweed","environmental"],["Tree Pollen","environmental"],["Grass Pollen","environmental"],["Cat","animal"],[... | SELECT allergy , allergytype FROM Allergy_type <table_name> : Allergy_Type col : Allergy | AllergyType row 1 : Eggs | food row 2 : Nuts | food row 3 : Milk | food row 4 : Shellfish | food row 5 : Anchovies | food row 6 : Wheat | food row 7 : Soy | food row 8 : Ragweed | environmental row 9 : Tree Pollen | environmenta... | col : Allergy | AllergyType row 1 : Eggs | food row 2 : Nuts | food row 3 : Milk | food row 4 : Shellfish | food row 5 : Anchovies | food row 6 : Wheat | food row 7 : Soy | food row 8 : Ragweed | environmental row 9 : Tree Pollen | environmental row 10 : Grass Pollen | environmental row 11 : Cat | animal row 12 : Dog |... |
SELECT DISTINCT allergy FROM Allergy_type WHERE allergytype = "food" | [
"Allergy_Type"
] | [
"{\"columns\":[\"Allergy\",\"AllergyType\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[\"Eggs\",\"food\"],[\"Nuts\",\"food\"],[\"Milk\",\"food\"],[\"Shellfish\",\"food\"],[\"Anchovies\",\"food\"],[\"Wheat\",\"food\"],[\"Soy\",\"food\"],[\"Ragweed\",\"environmental\"],[\"Tree Pollen\",\"environmental\"],... | {"columns":["Allergy"],"index":[0,1,2,3,4,5,6],"data":[["Anchovies"],["Eggs"],["Milk"],["Nuts"],["Shellfish"],["Soy"],["Wheat"]]} | SELECT DISTINCT allergy FROM Allergy_type WHERE allergytype = "food" <table_name> : Allergy_Type col : Allergy | AllergyType row 1 : Eggs | food row 2 : Nuts | food row 3 : Milk | food row 4 : Shellfish | food row 5 : Anchovies | food row 6 : Wheat | food row 7 : Soy | food row 8 : Ragweed | environmental row 9 : Tre... | col : Allergy row 1 : Anchovies row 2 : Eggs row 3 : Milk row 4 : Nuts row 5 : Shellfish row 6 : Soy row 7 : Wheat |
SELECT allergytype FROM Allergy_type WHERE allergy = "Cat" | [
"Allergy_Type"
] | [
"{\"columns\":[\"Allergy\",\"AllergyType\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[\"Eggs\",\"food\"],[\"Nuts\",\"food\"],[\"Milk\",\"food\"],[\"Shellfish\",\"food\"],[\"Anchovies\",\"food\"],[\"Wheat\",\"food\"],[\"Soy\",\"food\"],[\"Ragweed\",\"environmental\"],[\"Tree Pollen\",\"environmental\"],... | {"columns":["AllergyType"],"index":[0],"data":[["animal"]]} | SELECT allergytype FROM Allergy_type WHERE allergy = "Cat" <table_name> : Allergy_Type col : Allergy | AllergyType row 1 : Eggs | food row 2 : Nuts | food row 3 : Milk | food row 4 : Shellfish | food row 5 : Anchovies | food row 6 : Wheat | food row 7 : Soy | food row 8 : Ragweed | environmental row 9 : Tree Pollen |... | col : AllergyType row 1 : animal |
SELECT count(*) FROM Allergy_type WHERE allergytype = "animal" | [
"Allergy_Type"
] | [
"{\"columns\":[\"Allergy\",\"AllergyType\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[\"Eggs\",\"food\"],[\"Nuts\",\"food\"],[\"Milk\",\"food\"],[\"Shellfish\",\"food\"],[\"Anchovies\",\"food\"],[\"Wheat\",\"food\"],[\"Soy\",\"food\"],[\"Ragweed\",\"environmental\"],[\"Tree Pollen\",\"environmental\"],... | {"columns":["count(*)"],"index":[0],"data":[[4]]} | SELECT count(*) FROM Allergy_type WHERE allergytype = "animal" <table_name> : Allergy_Type col : Allergy | AllergyType row 1 : Eggs | food row 2 : Nuts | food row 3 : Milk | food row 4 : Shellfish | food row 5 : Anchovies | food row 6 : Wheat | food row 7 : Soy | food row 8 : Ragweed | environmental row 9 : Tree Poll... | col : count(*) row 1 : 4 |
SELECT allergytype , count(*) FROM Allergy_type GROUP BY allergytype | [
"Allergy_Type"
] | [
"{\"columns\":[\"Allergy\",\"AllergyType\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[\"Eggs\",\"food\"],[\"Nuts\",\"food\"],[\"Milk\",\"food\"],[\"Shellfish\",\"food\"],[\"Anchovies\",\"food\"],[\"Wheat\",\"food\"],[\"Soy\",\"food\"],[\"Ragweed\",\"environmental\"],[\"Tree Pollen\",\"environmental\"],... | {"columns":["AllergyType","count(*)"],"index":[0,1,2],"data":[["animal",4],["environmental",3],["food",7]]} | SELECT allergytype , count(*) FROM Allergy_type GROUP BY allergytype <table_name> : Allergy_Type col : Allergy | AllergyType row 1 : Eggs | food row 2 : Nuts | food row 3 : Milk | food row 4 : Shellfish | food row 5 : Anchovies | food row 6 : Wheat | food row 7 : Soy | food row 8 : Ragweed | environmental row 9 : Tree... | col : AllergyType | count(*) row 1 : animal | 4 row 2 : environmental | 3 row 3 : food | 7 |
SELECT allergytype FROM Allergy_type GROUP BY allergytype ORDER BY count(*) DESC LIMIT 1 | [
"Allergy_Type"
] | [
"{\"columns\":[\"Allergy\",\"AllergyType\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[\"Eggs\",\"food\"],[\"Nuts\",\"food\"],[\"Milk\",\"food\"],[\"Shellfish\",\"food\"],[\"Anchovies\",\"food\"],[\"Wheat\",\"food\"],[\"Soy\",\"food\"],[\"Ragweed\",\"environmental\"],[\"Tree Pollen\",\"environmental\"],... | {"columns":["AllergyType"],"index":[0],"data":[["food"]]} | SELECT allergytype FROM Allergy_type GROUP BY allergytype ORDER BY count(*) DESC LIMIT 1 <table_name> : Allergy_Type col : Allergy | AllergyType row 1 : Eggs | food row 2 : Nuts | food row 3 : Milk | food row 4 : Shellfish | food row 5 : Anchovies | food row 6 : Wheat | food row 7 : Soy | food row 8 : Ragweed | environ... | col : AllergyType row 1 : food |
SELECT allergytype FROM Allergy_type GROUP BY allergytype ORDER BY count(*) ASC LIMIT 1 | [
"Allergy_Type"
] | [
"{\"columns\":[\"Allergy\",\"AllergyType\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[\"Eggs\",\"food\"],[\"Nuts\",\"food\"],[\"Milk\",\"food\"],[\"Shellfish\",\"food\"],[\"Anchovies\",\"food\"],[\"Wheat\",\"food\"],[\"Soy\",\"food\"],[\"Ragweed\",\"environmental\"],[\"Tree Pollen\",\"environmental\"],... | {"columns":["AllergyType"],"index":[0],"data":[["environmental"]]} | SELECT allergytype FROM Allergy_type GROUP BY allergytype ORDER BY count(*) ASC LIMIT 1 <table_name> : Allergy_Type col : Allergy | AllergyType row 1 : Eggs | food row 2 : Nuts | food row 3 : Milk | food row 4 : Shellfish | food row 5 : Anchovies | food row 6 : Wheat | food row 7 : Soy | food row 8 : Ragweed | environm... | col : AllergyType row 1 : environmental |
SELECT count(*) FROM Student | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["count(*)"],"index":[0],"data":[[34]]} | SELECT count(*) FROM Student <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600 | 7792 | WAS row 4 : 1004 | Kumar | Dines... | col : count(*) row 1 : 34 |
SELECT Fname , Lname FROM Student | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["Fname","LName"],"index":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],"data":[["Linda","Smith"],["Tracy","Kim"],["Shiela","Jones"],["Dinesh","Kumar"],["Paul","Gompers"],["Andy","Schultz"],["Lisa","Apap"],["Jandy","Nelson"],["Eric","Tai"],["Derek","Lee"],["Dav... | SELECT Fname , Lname FROM Student <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600 | 7792 | WAS row 4 : 1004 | Kumar |... | col : Fname | LName row 1 : Linda | Smith row 2 : Tracy | Kim row 3 : Shiela | Jones row 4 : Dinesh | Kumar row 5 : Paul | Gompers row 6 : Andy | Schultz row 7 : Lisa | Apap row 8 : Jandy | Nelson row 9 : Eric | Tai row 10 : Derek | Lee row 11 : David | Adams row 12 : Steven | Davis row 13 : Charles | Norris row 14 : S... |
SELECT count(DISTINCT advisor) FROM Student | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["count(DISTINCT advisor)"],"index":[0],"data":[[18]]} | SELECT count(DISTINCT advisor) FROM Student <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600 | 7792 | WAS row 4 : 1004 ... | col : count(DISTINCT advisor) row 1 : 18 |
SELECT DISTINCT Major FROM Student | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["Major"],"index":[0,1,2,3,4,5],"data":[[600],[520],[540],[550],[100],[50]]} | SELECT DISTINCT Major FROM Student <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600 | 7792 | WAS row 4 : 1004 | Kumar |... | col : Major row 1 : 600 row 2 : 520 row 3 : 540 row 4 : 550 row 5 : 100 row 6 : 50 |
SELECT DISTINCT city_code FROM Student | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["city_code"],"index":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18],"data":[["BAL"],["HKG"],["WAS"],["CHI"],["YYZ"],["PIT"],["HOU"],["PHL"],["DAL"],["DET"],["LON"],["NYC"],["LOS"],["ROC"],["PEK"],["SFO"],["ATL"],["NAR"],["BOS"]]} | SELECT DISTINCT city_code FROM Student <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600 | 7792 | WAS row 4 : 1004 | Kum... | col : city_code row 1 : BAL row 2 : HKG row 3 : WAS row 4 : CHI row 5 : YYZ row 6 : PIT row 7 : HOU row 8 : PHL row 9 : DAL row 10 : DET row 11 : LON row 12 : NYC row 13 : LOS row 14 : ROC row 15 : PEK row 16 : SFO row 17 : ATL row 18 : NAR row 19 : BOS |
SELECT Fname , Lname , Age FROM Student WHERE Sex = 'F' | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["Fname","LName","Age"],"index":[0,1,2,3,4,5,6,7,8,9],"data":[["Linda","Smith",18],["Tracy","Kim",19],["Shiela","Jones",21],["Lisa","Apap",18],["Jandy","Nelson",20],["Susan","Lee",16],["Stacy","Prater",18],["Lisa","Cheng",21],["Sarah","Smith",20],["Sarah","Schmidt",26]]} | SELECT Fname , Lname , Age FROM Student WHERE Sex = 'F' <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600 | 7792 | W... | col : Fname | LName | Age row 1 : Linda | Smith | 18 row 2 : Tracy | Kim | 19 row 3 : Shiela | Jones | 21 row 4 : Lisa | Apap | 18 row 5 : Jandy | Nelson | 20 row 6 : Susan | Lee | 16 row 7 : Stacy | Prater | 18 row 8 : Lisa | Cheng | 21 row 9 : Sarah | Smith | 20 row 10 : Sarah | Schmidt | 26 |
SELECT StuID FROM Student WHERE Sex = 'M' | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["StuID"],"index":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23],"data":[[1004],[1005],[1006],[1009],[1010],[1011],[1012],[1014],[1016],[1017],[1018],[1019],[1020],[1021],[1022],[1023],[1025],[1026],[1027],[1028],[1029],[1032],[1033],[1034]]} | SELECT StuID FROM Student WHERE Sex = 'M' <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600 | 7792 | WAS row 4 : 1004 ... | col : StuID row 1 : 1004 row 2 : 1005 row 3 : 1006 row 4 : 1009 row 5 : 1010 row 6 : 1011 row 7 : 1012 row 8 : 1014 row 9 : 1016 row 10 : 1017 row 11 : 1018 row 12 : 1019 row 13 : 1020 row 14 : 1021 row 15 : 1022 row 16 : 1023 row 17 : 1025 row 18 : 1026 row 19 : 1027 row 20 : 1028 row 21 : 1029 row 22 : 1032 row 23 : ... |
SELECT count(*) FROM Student WHERE age = 18 | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["count(*)"],"index":[0],"data":[[10]]} | SELECT count(*) FROM Student WHERE age = 18 <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600 | 7792 | WAS row 4 : 100... | col : count(*) row 1 : 10 |
SELECT StuID FROM Student WHERE age > 20 | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["StuID"],"index":[0,1,2,3,4,5,6],"data":[[1003],[1005],[1011],[1017],[1020],[1030],[1035]]} | SELECT StuID FROM Student WHERE age > 20 <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600 | 7792 | WAS row 4 : 1004 |... | col : StuID row 1 : 1003 row 2 : 1005 row 3 : 1011 row 4 : 1017 row 5 : 1020 row 6 : 1030 row 7 : 1035 |
SELECT city_code FROM Student WHERE LName = "Kim" | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["city_code"],"index":[0],"data":[["HKG"]]} | SELECT city_code FROM Student WHERE LName = "Kim" <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600 | 7792 | WAS row 4... | col : city_code row 1 : HKG |
SELECT Advisor FROM Student WHERE StuID = 1004 | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["Advisor"],"index":[0],"data":[[8423]]} | SELECT Advisor FROM Student WHERE StuID = 1004 <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600 | 7792 | WAS row 4 : ... | col : Advisor row 1 : 8423 |
SELECT count(*) FROM Student WHERE city_code = "HKG" OR city_code = "CHI" | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["count(*)"],"index":[0],"data":[[4]]} | SELECT count(*) FROM Student WHERE city_code = "HKG" OR city_code = "CHI" <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | ... | col : count(*) row 1 : 4 |
SELECT min(age) , avg(age) , max(age) FROM Student | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["min(age)","avg(age)","max(age)"],"index":[0],"data":[[16,19.5588235294,27]]} | SELECT min(age) , avg(age) , max(age) FROM Student <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600 | 7792 | WAS row ... | col : min(age) | avg(age) | max(age) row 1 : 16 | 19.5588235294 | 27 |
SELECT LName FROM Student WHERE age = (SELECT min(age) FROM Student) | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["LName"],"index":[0],"data":[["Lee"]]} | SELECT LName FROM Student WHERE age = (SELECT min(age) FROM Student) <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600... | col : LName row 1 : Lee |
SELECT StuID FROM Student WHERE age = (SELECT max(age) FROM Student) | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["StuID"],"index":[0],"data":[[1017]]} | SELECT StuID FROM Student WHERE age = (SELECT max(age) FROM Student) <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600... | col : StuID row 1 : 1017 |
SELECT major , count(*) FROM Student GROUP BY major | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["Major","count(*)"],"index":[0,1,2,3,4,5],"data":[[50,2],[100,1],[520,6],[540,2],[550,5],[600,18]]} | SELECT major , count(*) FROM Student GROUP BY major <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600 | 7792 | WAS row ... | col : Major | count(*) row 1 : 50 | 2 row 2 : 100 | 1 row 3 : 520 | 6 row 4 : 540 | 2 row 5 : 550 | 5 row 6 : 600 | 18 |
SELECT major FROM Student GROUP BY major ORDER BY count(*) DESC LIMIT 1 | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["Major"],"index":[0],"data":[[600]]} | SELECT major FROM Student GROUP BY major ORDER BY count(*) DESC LIMIT 1 <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 60... | col : Major row 1 : 600 |
SELECT age , count(*) FROM Student GROUP BY age | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["Age","count(*)"],"index":[0,1,2,3,4,5,6,7,8],"data":[[16,1],[17,4],[18,10],[19,4],[20,8],[21,2],[22,2],[26,2],[27,1]]} | SELECT age , count(*) FROM Student GROUP BY age <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600 | 7792 | WAS row 4 : ... | col : Age | count(*) row 1 : 16 | 1 row 2 : 17 | 4 row 3 : 18 | 10 row 4 : 19 | 4 row 5 : 20 | 8 row 6 : 21 | 2 row 7 : 22 | 2 row 8 : 26 | 2 row 9 : 27 | 1 |
SELECT avg(age) , sex FROM Student GROUP BY sex | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["avg(age)","Sex"],"index":[0,1],"data":[[19.7,"F"],[19.5,"M"]]} | SELECT avg(age) , sex FROM Student GROUP BY sex <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600 | 7792 | WAS row 4 : ... | col : avg(age) | Sex row 1 : 19.7 | F row 2 : 19.5 | M |
SELECT city_code , count(*) FROM Student GROUP BY city_code | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["city_code","count(*)"],"index":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18],"data":[["ATL",1],["BAL",4],["BOS",1],["CHI",1],["DAL",1],["DET",1],["HKG",3],["HOU",1],["LON",1],["LOS",1],["NAR",1],["NYC",3],["PEK",1],["PHL",3],["PIT",4],["ROC",1],["SFO",1],["WAS",3],["YYZ",2]]} | SELECT city_code , count(*) FROM Student GROUP BY city_code <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600 | 7792 | ... | col : city_code | count(*) row 1 : ATL | 1 row 2 : BAL | 4 row 3 : BOS | 1 row 4 : CHI | 1 row 5 : DAL | 1 row 6 : DET | 1 row 7 : HKG | 3 row 8 : HOU | 1 row 9 : LON | 1 row 10 : LOS | 1 row 11 : NAR | 1 row 12 : NYC | 3 row 13 : PEK | 1 row 14 : PHL | 3 row 15 : PIT | 4 row 16 : ROC | 1 row 17 : SFO | 1 row 18 : WAS ... |
SELECT advisor , count(*) FROM Student GROUP BY advisor | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["Advisor","count(*)"],"index":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17],"data":[[1121,3],[1148,3],[2192,4],[2311,3],[5718,2],[7134,2],[7271,2],[7712,1],[7723,1],[7792,1],[8423,1],[8721,1],[8722,3],[8723,1],[8741,1],[8772,3],[8918,1],[9172,1]]} | SELECT advisor , count(*) FROM Student GROUP BY advisor <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F | 600 | 7792 | WAS ... | col : Advisor | count(*) row 1 : 1121 | 3 row 2 : 1148 | 3 row 3 : 2192 | 4 row 4 : 2311 | 3 row 5 : 5718 | 2 row 6 : 7134 | 2 row 7 : 7271 | 2 row 8 : 7712 | 1 row 9 : 7723 | 1 row 10 : 7792 | 1 row 11 : 8423 | 1 row 12 : 8721 | 1 row 13 : 8722 | 3 row 14 : 8723 | 1 row 15 : 8741 | 1 row 16 : 8772 | 3 row 17 : 8918 | ... |
SELECT advisor FROM Student GROUP BY advisor ORDER BY count(*) DESC LIMIT 1 | [
"Student"
] | [
"{\"columns\":[\"StuID\",\"LName\",\"Fname\",\"Age\",\"Sex\",\"Major\",\"Advisor\",\"city_code\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33],\"data\":[[1001,\"Smith\",\"Linda\",18,\"F\",600,1121,\"BAL\"],[1002,\"Kim\",\"Tracy\",19,\"F\",600,7712,\"HKG\"],... | {"columns":["Advisor"],"index":[0],"data":[[2192]]} | SELECT advisor FROM Student GROUP BY advisor ORDER BY count(*) DESC LIMIT 1 <table_name> : Student col : StuID | LName | Fname | Age | Sex | Major | Advisor | city_code row 1 : 1001 | Smith | Linda | 18 | F | 600 | 1121 | BAL row 2 : 1002 | Kim | Tracy | 19 | F | 600 | 7712 | HKG row 3 : 1003 | Jones | Shiela | 21 | F ... | col : Advisor row 1 : 2192 |
SELECT count(*) FROM Has_allergy WHERE Allergy = "Cat" | [
"Has_Allergy"
] | [
"{\"columns\":[\"StuID\",\"Allergy\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58],\"data\":[[1001,\"Cat\"],[1002,\"Shellfish\"],[1002,\"Tree Pollen\"],[1003,\"Dog\"],[1004,\"Nuts\"]... | {"columns":["count(*)"],"index":[0],"data":[[4]]} | SELECT count(*) FROM Has_allergy WHERE Allergy = "Cat" <table_name> : Has_Allergy col : StuID | Allergy row 1 : 1001 | Cat row 2 : 1002 | Shellfish row 3 : 1002 | Tree Pollen row 4 : 1003 | Dog row 5 : 1004 | Nuts row 6 : 1005 | Nuts row 7 : 1005 | Tree Pollen row 8 : 1006 | Nuts row 9 : 1007 | Ragweed row 10 : 1007 ... | col : count(*) row 1 : 4 |
SELECT StuID FROM Has_allergy GROUP BY StuID HAVING count(*) >= 2 | [
"Has_Allergy"
] | [
"{\"columns\":[\"StuID\",\"Allergy\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58],\"data\":[[1001,\"Cat\"],[1002,\"Shellfish\"],[1002,\"Tree Pollen\"],[1003,\"Dog\"],[1004,\"Nuts\"]... | {"columns":["StuID"],"index":[0,1,2,3,4,5,6,7,8,9,10,11],"data":[[1002],[1005],[1007],[1010],[1015],[1016],[1018],[1022],[1023],[1024],[1029],[1031]]} | SELECT StuID FROM Has_allergy GROUP BY StuID HAVING count(*) >= 2 <table_name> : Has_Allergy col : StuID | Allergy row 1 : 1001 | Cat row 2 : 1002 | Shellfish row 3 : 1002 | Tree Pollen row 4 : 1003 | Dog row 5 : 1004 | Nuts row 6 : 1005 | Nuts row 7 : 1005 | Tree Pollen row 8 : 1006 | Nuts row 9 : 1007 | Ragweed row... | col : StuID row 1 : 1002 row 2 : 1005 row 3 : 1007 row 4 : 1010 row 5 : 1015 row 6 : 1016 row 7 : 1018 row 8 : 1022 row 9 : 1023 row 10 : 1024 row 11 : 1029 row 12 : 1031 |
SELECT StuID FROM Student EXCEPT SELECT StuID FROM Has_allergy | [
"Has_Allergy",
"Student"
] | [
"{\"columns\":[\"StuID\",\"Allergy\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58],\"data\":[[1001,\"Cat\"],[1002,\"Shellfish\"],[1002,\"Tree Pollen\"],[1003,\"Dog\"],[1004,\"Nuts\"]... | {"columns":["StuID"],"index":[0,1,2,3,4],"data":[[1008],[1032],[1033],[1034],[1035]]} | SELECT StuID FROM Student EXCEPT SELECT StuID FROM Has_allergy <table_name> : Has_Allergy col : StuID | Allergy row 1 : 1001 | Cat row 2 : 1002 | Shellfish row 3 : 1002 | Tree Pollen row 4 : 1003 | Dog row 5 : 1004 | Nuts row 6 : 1005 | Nuts row 7 : 1005 | Tree Pollen row 8 : 1006 | Nuts row 9 : 1007 | Ragweed row 10 :... | col : StuID row 1 : 1008 row 2 : 1032 row 3 : 1033 row 4 : 1034 row 5 : 1035 |
SELECT count(*) FROM has_allergy AS T1 JOIN Student AS T2 ON T1.StuID = T2.StuID WHERE T2.sex = "F" AND T1.allergy = "Milk" OR T1.allergy = "Eggs" | [
"Has_Allergy",
"Student"
] | [
"{\"columns\":[\"StuID\",\"Allergy\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58],\"data\":[[1001,\"Cat\"],[1002,\"Shellfish\"],[1002,\"Tree Pollen\"],[1003,\"Dog\"],[1004,\"Nuts\"]... | {"columns":["count(*)"],"index":[0],"data":[[4]]} | SELECT count(*) FROM has_allergy AS T1 JOIN Student AS T2 ON T1.StuID = T2.StuID WHERE T2.sex = "F" AND T1.allergy = "Milk" OR T1.allergy = "Eggs" <table_name> : Has_Allergy col : StuID | Allergy row 1 : 1001 | Cat row 2 : 1002 | Shellfish row 3 : 1002 | Tree Pollen row 4 : 1003 | Dog row 5 : 1004 | Nuts row 6 ... | col : count(*) row 1 : 4 |
SELECT count(*) FROM Has_allergy AS T1 JOIN Allergy_type AS T2 ON T1.allergy = T2.allergy WHERE T2.allergytype = "food" | [
"Allergy_Type",
"Has_Allergy"
] | [
"{\"columns\":[\"Allergy\",\"AllergyType\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[\"Eggs\",\"food\"],[\"Nuts\",\"food\"],[\"Milk\",\"food\"],[\"Shellfish\",\"food\"],[\"Anchovies\",\"food\"],[\"Wheat\",\"food\"],[\"Soy\",\"food\"],[\"Ragweed\",\"environmental\"],[\"Tree Pollen\",\"environmental\"],... | {"columns":["count(*)"],"index":[0],"data":[[28]]} | SELECT count(*) FROM Has_allergy AS T1 JOIN Allergy_type AS T2 ON T1.allergy = T2.allergy WHERE T2.allergytype = "food" <table_name> : Allergy_Type col : Allergy | AllergyType row 1 : Eggs | food row 2 : Nuts | food row 3 : Milk | food row 4 : Shellfish | food row 5 : Anchovies | food row 6 : Wheat | food row 7 : S... | col : count(*) row 1 : 28 |
SELECT Allergy FROM Has_allergy GROUP BY Allergy ORDER BY count(*) DESC LIMIT 1 | [
"Has_Allergy"
] | [
"{\"columns\":[\"StuID\",\"Allergy\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58],\"data\":[[1001,\"Cat\"],[1002,\"Shellfish\"],[1002,\"Tree Pollen\"],[1003,\"Dog\"],[1004,\"Nuts\"]... | {"columns":["Allergy"],"index":[0],"data":[["Tree Pollen"]]} | SELECT Allergy FROM Has_allergy GROUP BY Allergy ORDER BY count(*) DESC LIMIT 1 <table_name> : Has_Allergy col : StuID | Allergy row 1 : 1001 | Cat row 2 : 1002 | Shellfish row 3 : 1002 | Tree Pollen row 4 : 1003 | Dog row 5 : 1004 | Nuts row 6 : 1005 | Nuts row 7 : 1005 | Tree Pollen row 8 : 1006 | Nuts row 9 : 1007 |... | col : Allergy row 1 : Tree Pollen |
SELECT Allergy , count(*) FROM Has_allergy GROUP BY Allergy | [
"Has_Allergy"
] | [
"{\"columns\":[\"StuID\",\"Allergy\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58],\"data\":[[1001,\"Cat\"],[1002,\"Shellfish\"],[1002,\"Tree Pollen\"],[1003,\"Dog\"],[1004,\"Nuts\"]... | {"columns":["Allergy","count(*)"],"index":[0,1,2,3,4,5,6,7,8,9,10,11],"data":[["Anchovies",3],["Cat",4],["Dog",3],["Eggs",3],["Grass Pollen",4],["Milk",3],["Nuts",11],["Ragweed",6],["Rodent",1],["Shellfish",4],["Soy",4],["Tree Pollen",13]]} | SELECT Allergy , count(*) FROM Has_allergy GROUP BY Allergy <table_name> : Has_Allergy col : StuID | Allergy row 1 : 1001 | Cat row 2 : 1002 | Shellfish row 3 : 1002 | Tree Pollen row 4 : 1003 | Dog row 5 : 1004 | Nuts row 6 : 1005 | Nuts row 7 : 1005 | Tree Pollen row 8 : 1006 | Nuts row 9 : 1007 | Ragweed row 10 : 1... | col : Allergy | count(*) row 1 : Anchovies | 3 row 2 : Cat | 4 row 3 : Dog | 3 row 4 : Eggs | 3 row 5 : Grass Pollen | 4 row 6 : Milk | 3 row 7 : Nuts | 11 row 8 : Ragweed | 6 row 9 : Rodent | 1 row 10 : Shellfish | 4 row 11 : Soy | 4 row 12 : Tree Pollen | 13 |
SELECT T2.allergytype , count(*) FROM Has_allergy AS T1 JOIN Allergy_type AS T2 ON T1.allergy = T2.allergy GROUP BY T2.allergytype | [
"Allergy_Type",
"Has_Allergy"
] | [
"{\"columns\":[\"Allergy\",\"AllergyType\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[\"Eggs\",\"food\"],[\"Nuts\",\"food\"],[\"Milk\",\"food\"],[\"Shellfish\",\"food\"],[\"Anchovies\",\"food\"],[\"Wheat\",\"food\"],[\"Soy\",\"food\"],[\"Ragweed\",\"environmental\"],[\"Tree Pollen\",\"environmental\"],... | {"columns":["AllergyType","count(*)"],"index":[0,1,2],"data":[["animal",8],["environmental",23],["food",28]]} | SELECT T2.allergytype , count(*) FROM Has_allergy AS T1 JOIN Allergy_type AS T2 ON T1.allergy = T2.allergy GROUP BY T2.allergytype <table_name> : Allergy_Type col : Allergy | AllergyType row 1 : Eggs | food row 2 : Nuts | food row 3 : Milk | food row 4 : Shellfish | food row 5 : Anchovies | food row 6 : Wheat | food... | col : AllergyType | count(*) row 1 : animal | 8 row 2 : environmental | 23 row 3 : food | 28 |
SELECT lname , age FROM Student WHERE StuID IN (SELECT StuID FROM Has_allergy WHERE Allergy = "Milk" INTERSECT SELECT StuID FROM Has_allergy WHERE Allergy = "Cat") | [
"Has_Allergy",
"Student"
] | [
"{\"columns\":[\"StuID\",\"Allergy\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58],\"data\":[[1001,\"Cat\"],[1002,\"Shellfish\"],[1002,\"Tree Pollen\"],[1003,\"Dog\"],[1004,\"Nuts\"]... | {"columns":["LName","Age"],"index":[0,1],"data":[["Apap",18],["Lee",17]]} | SELECT lname , age FROM Student WHERE StuID IN (SELECT StuID FROM Has_allergy WHERE Allergy = "Milk" INTERSECT SELECT StuID FROM Has_allergy WHERE Allergy = "Cat") <table_name> : Has_Allergy col : StuID | Allergy row 1 : 1001 | Cat row 2 : 1002 | Shellfish row 3 : 1002 | Tree Pollen row 4 : 1003 | Dog row 5 : 1004... | col : LName | Age row 1 : Apap | 18 row 2 : Lee | 17 |
SELECT T1.Allergy , T1.AllergyType FROM Allergy_type AS T1 JOIN Has_allergy AS T2 ON T1.Allergy = T2.Allergy JOIN Student AS T3 ON T3.StuID = T2.StuID WHERE T3.Fname = "Lisa" ORDER BY T1.Allergy | [
"Allergy_Type",
"Has_Allergy",
"Student"
] | [
"{\"columns\":[\"Allergy\",\"AllergyType\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[\"Eggs\",\"food\"],[\"Nuts\",\"food\"],[\"Milk\",\"food\"],[\"Shellfish\",\"food\"],[\"Anchovies\",\"food\"],[\"Wheat\",\"food\"],[\"Soy\",\"food\"],[\"Ragweed\",\"environmental\"],[\"Tree Pollen\",\"environmental\"],... | {"columns":["Allergy","AllergyType"],"index":[0,1,2,3,4,5,6,7,8,9],"data":[["Anchovies","food"],["Cat","animal"],["Dog","animal"],["Eggs","food"],["Grass Pollen","environmental"],["Grass Pollen","environmental"],["Milk","food"],["Ragweed","environmental"],["Shellfish","food"],["Tree Pollen","environmental"]]} | SELECT T1.Allergy , T1.AllergyType FROM Allergy_type AS T1 JOIN Has_allergy AS T2 ON T1.Allergy = T2.Allergy JOIN Student AS T3 ON T3.StuID = T2.StuID WHERE T3.Fname = "Lisa" ORDER BY T1.Allergy <table_name> : Allergy_Type col : Allergy | AllergyType row 1 : Eggs | food row 2 : Nuts | food row 3 : Milk | food ro... | col : Allergy | AllergyType row 1 : Anchovies | food row 2 : Cat | animal row 3 : Dog | animal row 4 : Eggs | food row 5 : Grass Pollen | environmental row 6 : Grass Pollen | environmental row 7 : Milk | food row 8 : Ragweed | environmental row 9 : Shellfish | food row 10 : Tree Pollen | environmental |
SELECT fname , sex FROM Student WHERE StuID IN (SELECT StuID FROM Has_allergy WHERE Allergy = "Milk" EXCEPT SELECT StuID FROM Has_allergy WHERE Allergy = "Cat") | [
"Has_Allergy",
"Student"
] | [
"{\"columns\":[\"StuID\",\"Allergy\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58],\"data\":[[1001,\"Cat\"],[1002,\"Shellfish\"],[1002,\"Tree Pollen\"],[1003,\"Dog\"],[1004,\"Nuts\"]... | {"columns":["Fname","Sex"],"index":[0],"data":[["Mark","M"]]} | SELECT fname , sex FROM Student WHERE StuID IN (SELECT StuID FROM Has_allergy WHERE Allergy = "Milk" EXCEPT SELECT StuID FROM Has_allergy WHERE Allergy = "Cat") <table_name> : Has_Allergy col : StuID | Allergy row 1 : 1001 | Cat row 2 : 1002 | Shellfish row 3 : 1002 | Tree Pollen row 4 : 1003 | Dog row 5 : 1004 | ... | col : Fname | Sex row 1 : Mark | M |
SELECT avg(age) FROM Student WHERE StuID IN ( SELECT T1.StuID FROM Has_allergy AS T1 JOIN Allergy_Type AS T2 ON T1.Allergy = T2.Allergy WHERE T2.allergytype = "food" INTERSECT SELECT T1.StuID FROM Has_allergy AS T1 JOIN Allergy_Type AS T2 ON T1.Allergy = T2.Allergy WHERE T2.allergytype = "animal") | [
"Allergy_Type",
"Has_Allergy",
"Student"
] | [
"{\"columns\":[\"Allergy\",\"AllergyType\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[\"Eggs\",\"food\"],[\"Nuts\",\"food\"],[\"Milk\",\"food\"],[\"Shellfish\",\"food\"],[\"Anchovies\",\"food\"],[\"Wheat\",\"food\"],[\"Soy\",\"food\"],[\"Ragweed\",\"environmental\"],[\"Tree Pollen\",\"environmental\"],... | {"columns":["avg(age)"],"index":[0],"data":[[18.3333333333]]} | SELECT avg(age) FROM Student WHERE StuID IN ( SELECT T1.StuID FROM Has_allergy AS T1 JOIN Allergy_Type AS T2 ON T1.Allergy = T2.Allergy WHERE T2.allergytype = "food" INTERSECT SELECT T1.StuID FROM Has_allergy AS T1 JOIN Allergy_Type AS T2 ON T1.Allergy = T2.Allergy WHERE T2.allergytype = "animal") <table_name> ... | col : avg(age) row 1 : 18.3333333333 |
SELECT fname , lname FROM Student WHERE StuID NOT IN (SELECT T1.StuID FROM Has_allergy AS T1 JOIN Allergy_Type AS T2 ON T1.Allergy = T2.Allergy WHERE T2.allergytype = "food") | [
"Allergy_Type",
"Has_Allergy",
"Student"
] | [
"{\"columns\":[\"Allergy\",\"AllergyType\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[\"Eggs\",\"food\"],[\"Nuts\",\"food\"],[\"Milk\",\"food\"],[\"Shellfish\",\"food\"],[\"Anchovies\",\"food\"],[\"Wheat\",\"food\"],[\"Soy\",\"food\"],[\"Ragweed\",\"environmental\"],[\"Tree Pollen\",\"environmental\"],... | {"columns":["Fname","LName"],"index":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19],"data":[["Linda","Smith"],["Shiela","Jones"],["Jandy","Nelson"],["Eric","Tai"],["David","Adams"],["Steven","Davis"],["Bruce","Wilson"],["Arthur","Pang"],["Ian","Thornton"],["George","Andreou"],["Stacy","Prater"],["Mark","Goldman"],... | SELECT fname , lname FROM Student WHERE StuID NOT IN (SELECT T1.StuID FROM Has_allergy AS T1 JOIN Allergy_Type AS T2 ON T1.Allergy = T2.Allergy WHERE T2.allergytype = "food") <table_name> : Allergy_Type col : Allergy | AllergyType row 1 : Eggs | food row 2 : Nuts | food row 3 : Milk | food row 4 : Shellfish | food... | col : Fname | LName row 1 : Linda | Smith row 2 : Shiela | Jones row 3 : Jandy | Nelson row 4 : Eric | Tai row 5 : David | Adams row 6 : Steven | Davis row 7 : Bruce | Wilson row 8 : Arthur | Pang row 9 : Ian | Thornton row 10 : George | Andreou row 11 : Stacy | Prater row 12 : Mark | Goldman row 13 : Eric | Pang row 1... |
SELECT count(*) FROM Student WHERE sex = "M" AND StuID IN (SELECT StuID FROM Has_allergy AS T1 JOIN Allergy_Type AS T2 ON T1.Allergy = T2.Allergy WHERE T2.allergytype = "food") | [
"Allergy_Type",
"Has_Allergy",
"Student"
] | [
"{\"columns\":[\"Allergy\",\"AllergyType\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[\"Eggs\",\"food\"],[\"Nuts\",\"food\"],[\"Milk\",\"food\"],[\"Shellfish\",\"food\"],[\"Anchovies\",\"food\"],[\"Wheat\",\"food\"],[\"Soy\",\"food\"],[\"Ragweed\",\"environmental\"],[\"Tree Pollen\",\"environmental\"],... | {"columns":["count(*)"],"index":[0],"data":[[10]]} | SELECT count(*) FROM Student WHERE sex = "M" AND StuID IN (SELECT StuID FROM Has_allergy AS T1 JOIN Allergy_Type AS T2 ON T1.Allergy = T2.Allergy WHERE T2.allergytype = "food") <table_name> : Allergy_Type col : Allergy | AllergyType row 1 : Eggs | food row 2 : Nuts | food row 3 : Milk | food row 4 : Shellfish | f... | col : count(*) row 1 : 10 |
SELECT DISTINCT T1.fname , T1.city_code FROM Student AS T1 JOIN Has_Allergy AS T2 ON T1.stuid = T2.stuid WHERE T2.Allergy = "Milk" OR T2.Allergy = "Cat" | [
"Has_Allergy",
"Student"
] | [
"{\"columns\":[\"StuID\",\"Allergy\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58],\"data\":[[1001,\"Cat\"],[1002,\"Shellfish\"],[1002,\"Tree Pollen\"],[1003,\"Dog\"],[1004,\"Nuts\"]... | {"columns":["Fname","city_code"],"index":[0,1,2,3,4],"data":[["Linda","BAL"],["Lisa","PIT"],["Derek","HOU"],["Mark","DET"],["David","NYC"]]} | SELECT DISTINCT T1.fname , T1.city_code FROM Student AS T1 JOIN Has_Allergy AS T2 ON T1.stuid = T2.stuid WHERE T2.Allergy = "Milk" OR T2.Allergy = "Cat" <table_name> : Has_Allergy col : StuID | Allergy row 1 : 1001 | Cat row 2 : 1002 | Shellfish row 3 : 1002 | Tree Pollen row 4 : 1003 | Dog row 5 : 1004 | Nuts r... | col : Fname | city_code row 1 : Linda | BAL row 2 : Lisa | PIT row 3 : Derek | HOU row 4 : Mark | DET row 5 : David | NYC |
SELECT count(*) FROM Student WHERE age > 18 AND StuID NOT IN ( SELECT StuID FROM Has_allergy AS T1 JOIN Allergy_Type AS T2 ON T1.Allergy = T2.Allergy WHERE T2.allergytype = "food" OR T2.allergytype = "animal") | [
"Allergy_Type",
"Has_Allergy",
"Student"
] | [
"{\"columns\":[\"Allergy\",\"AllergyType\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13],\"data\":[[\"Eggs\",\"food\"],[\"Nuts\",\"food\"],[\"Milk\",\"food\"],[\"Shellfish\",\"food\"],[\"Anchovies\",\"food\"],[\"Wheat\",\"food\"],[\"Soy\",\"food\"],[\"Ragweed\",\"environmental\"],[\"Tree Pollen\",\"environmental\"],... | {"columns":["count(*)"],"index":[0],"data":[[12]]} | SELECT count(*) FROM Student WHERE age > 18 AND StuID NOT IN ( SELECT StuID FROM Has_allergy AS T1 JOIN Allergy_Type AS T2 ON T1.Allergy = T2.Allergy WHERE T2.allergytype = "food" OR T2.allergytype = "animal") <table_name> : Allergy_Type col : Allergy | AllergyType row 1 : Eggs | food row 2 : Nuts | food row 3 ... | col : count(*) row 1 : 12 |
SELECT fname , major FROM Student WHERE StuID NOT IN (SELECT StuID FROM Has_allergy WHERE Allergy = "Soy") | [
"Has_Allergy",
"Student"
] | [
"{\"columns\":[\"StuID\",\"Allergy\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58],\"data\":[[1001,\"Cat\"],[1002,\"Shellfish\"],[1002,\"Tree Pollen\"],[1003,\"Dog\"],[1004,\"Nuts\"]... | {"columns":["Fname","Major"],"index":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29],"data":[["Linda",600],["Tracy",600],["Shiela",600],["Dinesh",600],["Paul",600],["Andy",600],["Lisa",600],["Jandy",600],["Eric",600],["Derek",600],["David",600],["Steven",600],["Charles",600],["Mark",60... | SELECT fname , major FROM Student WHERE StuID NOT IN (SELECT StuID FROM Has_allergy WHERE Allergy = "Soy") <table_name> : Has_Allergy col : StuID | Allergy row 1 : 1001 | Cat row 2 : 1002 | Shellfish row 3 : 1002 | Tree Pollen row 4 : 1003 | Dog row 5 : 1004 | Nuts row 6 : 1005 | Nuts row 7 : 1005 | Tree Pollen row ... | col : Fname | Major row 1 : Linda | 600 row 2 : Tracy | 600 row 3 : Shiela | 600 row 4 : Dinesh | 600 row 5 : Paul | 600 row 6 : Andy | 600 row 7 : Lisa | 600 row 8 : Jandy | 600 row 9 : Eric | 600 row 10 : Derek | 600 row 11 : David | 600 row 12 : Steven | 600 row 13 : Charles | 600 row 14 : Mark | 600 row 15 : Bruce ... |
SELECT billing_country , COUNT(*) FROM invoices GROUP BY billing_country ORDER BY count(*) DESC LIMIT 5; | [
"invoices"
] | [
"{\"columns\":[\"id\",\"customer_id\",\"invoice_date\",\"billing_address\",\"billing_city\",\"billing_state\",\"billing_country\",\"billing_postal_code\",\"total\"],\"index\":[0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,... | {"columns":["billing_country","COUNT(*)"],"index":[0,1,2,3,4],"data":[["USA",91],["Canada",56],["Brazil",35],["France",35],["Germany",28]]} | SELECT billing_country , COUNT(*) FROM invoices GROUP BY billing_country ORDER BY count(*) DESC LIMIT 5; <table_name> : invoices col : id | customer_id | invoice_date | billing_address | billing_city | billing_state | billing_country | billing_postal_code | total row 1 : 1 | 2 | 2007-01-01 00:00:00 | Theodor-Heuss-Str... | col : billing_country | COUNT(*) row 1 : USA | 91 row 2 : Canada | 56 row 3 : Brazil | 35 row 4 : France | 35 row 5 : Germany | 28 |
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