In this tutorial, we'll look at how to remove the timezone info from a datetime column in a Pandas DataFrame.

The short answer of this questions is:

(1) Use method .dt.tz_localize(None)

df['time_tz'].dt.tz_localize(None)

(2) With .dt.tz_convert(None')

df['time_tz'].dt.tz_convert(None')

This will help you when you need to compare with another column which doesn't have timezone info. Otherwise you will get an errors like:

  • TypeError: Timestamp subtraction must have the same timezones or no timezones
  • TypeError: Invalid comparison between dtype=datetime64[ns] and DatetimeArray

Let's show simple example on removing the timezone information in Pandas.

Starting with creating DataFrame like:

import pandas as pd
import datetime
import pytz

dates = ['2021-08-01', '2021-08-02', '2021-08-03']

timestamps = [
    datetime.datetime(2021, 8, 1, 12, 30, 41, 775854, tzinfo=pytz.timezone('US/Pacific')),
    datetime.datetime(2021, 8, 2, 12, 31, 12, 432523, tzinfo=pytz.timezone('US/Pacific')),
    datetime.datetime(2021, 8, 3, 12, 29, 59, 123512, tzinfo=pytz.timezone('US/Pacific')),    
]

df = pd.DataFrame({'start_date': dates, 'time': timestamps})
df

Data:

start_date time time_tz
2021-08-01 2021-08-01 12:30:41.775854 2021-08-01 13:23:41.775854-07:00
2021-08-02 2021-08-02 12:31:12.432523 2021-08-02 13:24:12.432523-07:00
2021-08-03 2021-08-03 12:29:59.123512 2021-08-03 13:22:59.123512-07:00

Now let's check the data stored in column time:

0   2021-08-01 13:23:41.775854-07:00
1   2021-08-02 13:24:12.432523-07:00
2   2021-08-03 13:22:59.123512-07:00
Name: time, dtype: datetime64[ns, US/Pacific]

We have dtype: datetime64[ns, US/Pacific]

If you like to compare this information with another datetime column without the timezone info you will get an errors like:

  • TypeError: Timestamp subtraction must have the same timezones or no timezones
  • TypeError: Invalid comparison between dtype=datetime64[ns] and DatetimeArray

If you compare the column without the timezone info you will not face an error.

df['time'] > pd.to_datetime(df['start_date'])

working with timezone info is causing the errors mentioned above.

Remove TimeZone from DateTime column in Pandas

.dt.tz_localize(None)

In order to drop the timezone info from this column you can use:

df['time_tz'].dt.tz_localize(None)

which will result into:

0   2021-08-01 13:23:41.775854
1   2021-08-02 13:24:12.432523
2   2021-08-03 13:22:59.123512
Name: time_tz, dtype: datetime64[ns]

Now you can use this column without getting the errors mentioned above.

.dt.tz_convert(None)

Another option to deal with TimeZone info is by using the method: .dt.tz_convert('UTC'). You can delete or add the timezone info:

df['time_tz'].dt.tz_convert(None)

or

df['time_tz'].dt.tz_convert('UTC')

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