如何在 Pandas DataFrame 中设置值的时区? [英] How to set time zone of values in a Pandas DataFrame?

问题描述

我想设置 Pandas DataFrame 中列值的时区.我正在使用 pandas.read_csv() 读取 DataFrame.

I'd like to set the time zone of the values of a column in a Pandas DataFrame. I am reading the DataFrame with pandas.read_csv().

推荐答案

您可以直接从 read_csv 通过手动设置 date_parser 函数，例如:

You can read dates as UTC directly from read_csv by setting the date_parser function manually, for example:

from dateutil.tz import tzutc
from dateutil.parser import parse

def date_utc(s):
    return parse(s, tzinfos=tzutc)

df = read_csv('my.csv', parse_dates=[0], date_parser=date_utc)

.

如果您正在创建时间序列，则可以使用 date_range 的 tz 参数:

If you are creating a timeseries, you can use the tz argument of date_range:

dd = pd.date_range('2012-1-1 1:30', periods=3, freq='min', tz='UTC')

In [2]: dd
Out[2]: 
<class 'pandas.tseries.index.DatetimeIndex'>
[2012-01-01 01:30:00, ..., 2012-01-01 01:32:00]
Length: 3, Freq: T, Timezone: UTC

.

如果您的 DataFrame/Series 已经被时间序列索引，您可以使用 tz_localize 设置时区的方法:

If your DataFrame/Series is already index by a timeseries, you can use the tz_localize method to set a timezone:

df.tz_localize('UTC')

或者如果它已经有时区，请使用 tz_convert:

or if it already has a timezone, use tz_convert:

df.tz_convert('UTC')

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