numpy - How to set time zone of values in a Pandas DataFrame?

Question

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().

Answer 1

read_csv您可以通过手动设置函数直接将日期读取为 UTC date_parser，例如：

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，则可以使用以下tz参数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 已经按时间序列索引，则可以使用该tz_localize方法设置时区：

df.tz_localize('UTC')

或者如果它已经有一个时区，请使用tz_convert：

df.tz_convert('UTC')

Answer 2

# core modules
from datetime import timezone, datetime

# 3rd party modules
import pandas as pd
import pytz

# create a dummy dataframe
df = pd.DataFrame({'date': [datetime(2018, 12, 30, 20 + i, 56)
                            for i in range(2)]},)
print(df)

# Convert the time to a timezone-aware datetime object
df['date'] = df['date'].dt.tz_localize(timezone.utc)
print(df)

# Convert the time from to another timezone
# The point in time does not change, only the associated timezone
my_timezone = pytz.timezone('Europe/Berlin')
df['date'] = df['date'].dt.tz_convert(my_timezone)
print(df)

给

                 date
0 2018-12-30 20:56:00
1 2018-12-30 21:56:00
                       date
0 2018-12-30 20:56:00+00:00
1 2018-12-30 21:56:00+00:00
                       date
0 2018-12-30 21:56:00+01:00
1 2018-12-30 22:56:00+01:00

Answer 3

df['date'] = df['date'].dt.tz_localize('UTC')

这似乎从我的“天真”时区开始工作。