Title: Convert pandas Column's Time Zone
Slug: convert_pandas_column_timezone
Summary: How to convert the time zone of a pandas column/series in Python.
Date: 2017-09-11 12:00
Category: Machine Learning
Tags: Preprocessing Dates And Times
Authors: Chris Albon

Preliminaries



In [1]:

    
# Load libraries
import pandas as pd
from pytz import all_timezones

View Timezones



In [2]:

    
# Show ten time zones
all_timezones[0:10]









    Out[2]:





['Africa/Abidjan',
 'Africa/Accra',
 'Africa/Addis_Ababa',
 'Africa/Algiers',
 'Africa/Asmara',
 'Africa/Asmera',
 'Africa/Bamako',
 'Africa/Bangui',
 'Africa/Banjul',
 'Africa/Bissau']

Create pandas Series Of Dates



In [3]:

    
# Create ten dates
dates = pd.Series(pd.date_range('2/2/2002', periods=10, freq='M'))

Add Time Zone Of pandas Series



In [4]:

    
# Set time zone
dates_with_abidjan_time_zone = dates.dt.tz_localize('Africa/Abidjan')

# View pandas series
dates_with_abidjan_time_zone









    Out[4]:





0   2002-02-28 00:00:00+00:00
1   2002-03-31 00:00:00+00:00
2   2002-04-30 00:00:00+00:00
3   2002-05-31 00:00:00+00:00
4   2002-06-30 00:00:00+00:00
5   2002-07-31 00:00:00+00:00
6   2002-08-31 00:00:00+00:00
7   2002-09-30 00:00:00+00:00
8   2002-10-31 00:00:00+00:00
9   2002-11-30 00:00:00+00:00
dtype: datetime64[ns, Africa/Abidjan]

Convert Time Zone Of pandas Series



In [5]:

    
# Convert time zone
dates_with_london_time_zone = dates_with_abidjan_time_zone.dt.tz_convert('Europe/London')

# View pandas series
dates_with_london_time_zone









    Out[5]:





0   2002-02-28 00:00:00+00:00
1   2002-03-31 00:00:00+00:00
2   2002-04-30 01:00:00+01:00
3   2002-05-31 01:00:00+01:00
4   2002-06-30 01:00:00+01:00
5   2002-07-31 01:00:00+01:00
6   2002-08-31 01:00:00+01:00
7   2002-09-30 01:00:00+01:00
8   2002-10-31 00:00:00+00:00
9   2002-11-30 00:00:00+00:00
dtype: datetime64[ns, Europe/London]