.query()로 데이터 선택하기
pandas로 데이터 조인하기
Aaren Stubberfield
Instructor
.query() 메소드
.query('SOME SELECTION STATEMENT')
- 입력 문자열을 받습니다
- 입력 문자열은 반환되는 행을 결정하는 데 사용됩니다
- SQL 구문의 WHERE 절 뒤의 문장과 유사한 입력 문자열
- SQL에 대한 사전 지식은 필요하지 않습니다
단일 조건으로 쿼리하기
이 테이블은 stocks입니다
date disney nike
0 2019-07-01 143.009995 86.029999
1 2019-08-01 137.259995 84.5
2 2019-09-01 130.320007 93.919998
3 2019-10-01 129.919998 89.550003
4 2019-11-01 151.580002 93.489998
5 2019-12-01 144.630005 101.309998
6 2020-01-01 138.309998 96.300003
7 2020-02-01 117.650002 89.379997
8 2020-03-01 96.599998 82.739998
9 2020-04-01 99.580002 84.629997
stocks.query('nike >= 90')
date disney nike
2 2019-09-01 130.320007 93.919998
4 2019-11-01 151.580002 93.489998
5 2019-12-01 144.630005 101.309998
6 2020-01-01 138.309998 96.300003
여러 조건에서 쿼리하기, "and", "or"
이 테이블은 stocks입니다
date disney nike
0 2019-07-01 143.009995 86.029999
1 2019-08-01 137.259995 84.5
2 2019-09-01 130.320007 93.919998
3 2019-10-01 129.919998 89.550003
4 2019-11-01 151.580002 93.489998
5 2019-12-01 144.630005 101.309998
6 2020-01-01 138.309998 96.300003
7 2020-02-01 117.650002 89.379997
8 2020-03-01 96.599998 82.739998
9 2020-04-01 99.580002 84.629997
stocks.query('nike > 90 and disney < 140')
date disney nike
2 2019-09-01 130.320007 93.919998
6 2020-01-01 138.309998 96.300003
stocks.query('nike > 96 or disney < 98')
date disney nike
5 2019-12-01 144.630005 101.309998
6 2020-01-01 138.309998 96.300003
28 020-03-01 96.599998 82.739998
업데이트된 데이터세트
이 테이블은 stocks_long입니다
date stock close
0 2019-07-01 disney 143.009995
1 2019-08-01 disney 137.259995
2 2019-09-01 disney 130.320007
3 2019-10-01 disney 129.919998
4 2019-11-01 disney 151.580002
5 2019-07-01 nike 86.029999
6 2019-08-01 nike 84.5
7 2019-09-01 nike 93.919998
8 2019-10-01 nike 89.550003
9 2019-11-01 nike 93.489998
.query()를 사용하여 텍스트 선택하기
stocks_long.query('stock=="disney" or (stock=="nike" and close < 90)')
date stock close
0 2019-07-01 disney 143.009995
1 2019-08-01 disney 137.259995
2 2019-09-01 disney 130.320007
3 2019-10-01 disney 129.919998
4 2019-11-01 disney 151.580002
5 2019-07-01 nike 86.029999
6 2019-08-01 nike 84.5
8 2019-10-01 nike 89.550003
연습해 봅시다!
pandas로 데이터 조인하기
