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Python Pandas - Extract the timezone from the DateTimeIndex with specific time series frequency
To extract the timezone from the DateTimeIndex with specific time series frequency, use the DateTimeIndex.tz property.
At first, import the required libraries −
import pandas as pd
Create a DatetimeIndex with period 6 and frequency as D i.e. day. The timezone is Australia/Sydney −
datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=6, tz='Australia/Sydney', freq='D')
Display DateTimeIndex −
print("DateTimeIndex...\n", datetimeindex)Get the timezone −
print("\nGet the timezone..\n",datetimeindex.tz)
Example
Following is the code −
import pandas as pd
# DatetimeIndex with period 6 and frequency as D i.e. day
# The timezone is Australia/Sydney
datetimeindex = pd.date_range('2021-10-20 02:30:50', periods=6, tz='Australia/Sydney', freq='D')
# display DateTimeIndex
print("DateTimeIndex...\n", datetimeindex)
# display DateTimeIndex frequency
print("DateTimeIndex frequency...\n", datetimeindex.freq)
# Get the timezone
print("\nGet the timezone..\n",datetimeindex.tz)Output
This will produce the following code −
DateTimeIndex... DatetimeIndex(['2021-10-20 02:30:50+11:00', '2021-10-21 02:30:50+11:00', '2021-10-22 02:30:50+11:00', '2021-10-23 02:30:50+11:00', '2021-10-24 02:30:50+11:00', '2021-10-25 02:30:50+11:00'], dtype='datetime64[ns, Australia/Sydney]', freq='D') DateTimeIndex frequency... <Day> Get the timezone.. Australia/Sydney
Updated on: 18-Oct-2021
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