오우진

테이블 생성코드 Create table If Not Exists Sales (sale_id int, product_id int, year int, quantity int, price int) Create table If Not Exists Product (product_id int, product_name varchar(10)) Truncate table Sales insert into Sales (sale_id, product_id, year, quantity, price) values ('1', '100', '2008', '10', '5000') insert into Sales (sale_id, product_id, year, quantity, price) values ('2', '100', '200..

테이블 생성코드 data = [[1, 3, 5, '2019-08-01'], [1, 3, 6, '2019-08-02'], [2, 7, 7, '2019-08-01'], [2, 7, 6, '2019-08-02'], [4, 7, 1, '2019-07-22'], [3, 4, 4, '2019-07-21'], [3, 4, 4, '2019-07-21']] views = pd.DataFrame(data, columns=['article_id', 'author_id', 'viewer_id', 'view_date']).astype({'article_id':'Int64', 'author_id':'Int64', 'viewer_id':'Int64', 'view_date':'datetime64[ns]'}) 문제 해결 코드 1 de..

테이블 생성 코드 Create table If Not Exists Views (article_id int, author_id int, viewer_id int, view_date date) Truncate table Views insert into Views (article_id, author_id, viewer_id, view_date) values ('1', '3', '5', '2019-08-01') insert into Views (article_id, author_id, viewer_id, view_date) values ('1', '3', '6', '2019-08-02') insert into Views (article_id, author_id, viewer_id, view_date) value..

테이블 생성코드 data = [[1, 'War', 'great 3D', 8.9], [2, 'Science', 'fiction', 8.5], [3, 'irish', 'boring', 6.2], [4, 'Ice song', 'Fantacy', 8.6], [5, 'House card', 'Interesting', 9.1]] cinema = pd.DataFrame(data, columns=['id', 'movie', 'description', 'rating']).astype({'id':'Int64', 'movie':'object', 'description':'object', 'rating':'Float64'}) 문제 해결 코드 import pandas as pd def not_boring_movies(cinem..

EVEN NUMBER : 짝수 ODD NUMBER : 홀수 테이블 생성코드 Create table If Not Exists cinema (id int, movie varchar(255), description varchar(255), rating float(2, 1)) Truncate table cinema insert into cinema (id, movie, description, rating) values ('1', 'War', 'great 3D', '8.9') insert into cinema (id, movie, description, rating) values ('2', 'Science', 'fiction', '8.5') insert into cinema (id, movie, descripti..

테이블 생성코드 data = [[1, 'Wang', 'Allen'], [2, 'Alice', 'Bob']]person = pd.DataFrame(data, columns=['personId', 'firstName', 'lastName']).astype({'personId':'Int64', 'firstName':'object', 'lastName':'object'})data = [[1, 2, 'New York City', 'New York'], [2, 3, 'Leetcode', 'California']]address = pd.DataFrame(data, columns=['addressId', 'personId', 'city', 'state']).astype({'addressId':'Int64', 'pers..

테이블 생성 코드 data = [[1, 'a@b.com'], [2, 'c@d.com'], [3, 'a@b.com']] person = pd.DataFrame(data, columns=['id', 'email']).astype({'id':'Int64', 'email':'object'}) 문제 해결 코드 import pandas as pd def duplicate_emails(person: pd.DataFrame) -> pd.DataFrame: results = person.loc[person.duplicated(subset=['email']), ['email']] return results 풀이 results = 데이터프레임.loc[인덱스,['컬럼명']] 를 이용하였다,. 인덱스 = person.dupli..

테이블 생성 코드 Create table If Not Exists Person (personId int, firstName varchar(255), lastName varchar(255)) Create table If Not Exists Address (addressId int, personId int, city varchar(255), state varchar(255)) Truncate table Person insert into Person (personId, lastName, firstName) values ('1', 'Wang', 'Allen') insert into Person (personId, lastName, firstName) values ('2', 'Alice', 'Bob') Trunc..

테이블 생성코드 Create table If Not Exists World (name varchar(255), continent varchar(255), area int, population int, gdp bigint) Truncate table World insert into World (name, continent, area, population, gdp) values ('Afghanistan', 'Asia', '652230', '25500100', '20343000000') insert into World (name, continent, area, population, gdp) values ('Albania', 'Europe', '28748', '2831741', '12960000000') ins..

테이블 생성하기 Create table If Not Exists Person (id int, email varchar(255)) Truncate table Person insert into Person (id, email) values ('1', 'a@b.com') insert into Person (id, email) values ('2', 'c@d.com') insert into Person (id, email) values ('3', 'a@b.com') 문제 결과코드 # Write your MySQL query statement below SELECT email AS Email FROM Person GROUP BY Email HAVING COUNT(Email)>=2; 해설 GROUP BY로 emai..