판다스 시리즈에서 날짜(date)를 인덱스로 사용해 보자.1. 문자열을 인덱스로 사용해 보자.문자열을 인덱스로 사용할수 있다.문자열을 인덱스로 사용할때 주의점은 없는 날짜나 시간을 넣으면 에러가 날수 있다. 다음과 없는 날짜로 슬라이스 하면 에러가 난다. s['2024-04-20':'2024-04-29']) from pandas import Series
date = ['2024-04-20 00:00:00', '2024-04-22 00:00:00', '2024-04-29 00:00:30', '2025-05-10 00:00:00'] btc_close = [99900000, 91000000, 89000000, 99900000] s = Series(btc_close, index=date) #print('Series', s) #print('index = ', s.index) #print('value= ', s.values) print('----------------------------------------------') s['2024-04-21 00:00:30'] = 933000000 print('add', s) print('----------------------------------------------') s = s.drop('2024-04-22 00:00:00') print('drop', s) print('----------------------------------------------') print('slice', s[0: 2]) print('----------------------------------------------') #print('slice', s['2024-04-20':'2024-04-29']) #에러남 print('----------------------------------------------') print('slice', s['2024-04-20 00:00:00':'2024-04-29 00:00:30']) print('----------------------------------------------') print('average', s.mean()) print('나누기', s/10000) 결과) ---------------------------------------------- add 2024-04-20 00:00:00 99900000 2024-04-22 00:00:00 91000000 2024-04-29 00:00:30 89000000 2025-05-10 00:00:00 99900000 2024-04-21 00:00:30 933000000 dtype: int64 ---------------------------------------------- drop 2024-04-20 00:00:00 99900000 2024-04-29 00:00:30 89000000 2025-05-10 00:00:00 99900000 2024-04-21 00:00:30 933000000 dtype: int64 ---------------------------------------------- slice 2024-04-20 00:00:00 99900000 2024-04-29 00:00:30 89000000 dtype: int64 ---------------------------------------------- ---------------------------------------------- slice 2024-04-20 00:00:00 99900000 2024-04-29 00:00:30 89000000 dtype: int64 ---------------------------------------------- average 305450000.0 나누기 2024-04-20 00:00:00 9990.0 2024-04-29 00:00:30 8900.0 2025-05-10 00:00:00 9990.0 2024-04-21 00:00:30 93300.0 dtype: float64 2. datetime을 인덱스로 사용하기datetime은 시간이 완전히 같지 않아도 slice 할때 에러가 발생하지 않는다.s['2024-04-20':'2024-04-29'] from datetime import datetime
from pandas import Series dateStr = ['2024-04-20 00:00:00', '2024-04-22 00:00:00', '2024-04-29 00:00:30', '2025-05-10 00:00:00'] date = [] for value in dateStr: dateValue = datetime.strptime(value, '%Y-%m-%d %H:%M:%S') date.append(dateValue) btc_close = [99900000, 91000000, 89000000, 99900000] s = Series(btc_close, index=date) #print('index = ', s.index) #print('value= ', s.values) print('----------------------------------------------') value = '2024-04-21 00:00:30' dateValue = datetime.strptime(value, '%Y-%m-%d %H:%M:%S') s[dateValue] = 93000000 print('add', s) print('----------------------------------------------') print('성공 slice', s['2024-04-20':'2024-04-29']) print('----------------------------------------------') print('slice', s['2024-04-20':'2024-04-29 00:00:20']) print('----------------------------------------------') print('average', s.mean()) print('나누기', s/10000) 참조) 인덱스 삭제, 추가 https://jaeano.tistory.com/entry/Pandas-시리즈-2-Series |