2 回答

TA貢獻1788條經驗 獲得超4個贊
pandas.to_datetime如果你稍微調整一下字符串,應該會很高興地解析這個:
import pandas as pd
df = pd.DataFrame({"datepicker":[ "2019-09-07 16:00 UTC+2", "2019-09-04 18:30 UTC+4",
"2019-09-06 17:00 UTC±0", "2019-09-10 16:00 UTC+1",
"2019-09-04 18:00 UTC+3"]})
df['datetime'] = pd.to_datetime(df['datepicker'].str.replace('±', '+'))
# df['datetime']
# 0 2019-09-07 16:00:00-02:00
# 1 2019-09-04 18:30:00-04:00
# 2 2019-09-06 17:00:00+00:00
# 3 2019-09-10 16:00:00-01:00
# 4 2019-09-04 18:00:00-03:00
# Name: datetime, dtype: object
請注意,由于混合 UTC 偏移量,該列的數據類型為“對象”(日期時間對象)。如果您愿意,還可以立即轉換為 UTC,以獲得 dtype datetime[ns] 的列:
df['UTC'] = pd.to_datetime(df['datepicker'].str.replace('±', '+'), utc=True)
# df['UTC']
# 0 2019-09-07 18:00:00+00:00
# 1 2019-09-04 22:30:00+00:00
# 2 2019-09-06 17:00:00+00:00
# 3 2019-09-10 17:00:00+00:00
# 4 2019-09-04 21:00:00+00:00
# Name: UTC, dtype: datetime64[ns, UTC]

TA貢獻1770條經驗 獲得超3個贊
當我定義如下時。它按您的預期工作。
from datetime import datetime, timedelta, timezone
UTC = timezone(timedelta(hours=+3))
dt = datetime(2019, 1, 1, 12, 0, 0, tzinfo=UTC)
timestampStr = dt.strftime("%Y-%m-%d %H:%M %Z%z")
print(timestampStr)
輸出為:
2019-01-01 12:00 UTC+03:00+0300
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