Python Pandas - Convert the DateTimeIndex to Series excluding the TimeZone

To convert the DateTimeIndex to Series excluding the TimeZone, use the datetimeindex.tz_convert(None).to_series(). The tz.convert(None) is used to exclude the timezone.

At first, import the required libraries −

import pandas as pd

Create a DatetimeIndex with period 5 and frequency as S i.e. seconds −

datetimeindex = pd.date_range('2021-10-18 07:20:32.261811624', periods=5,
tz='Australia/Adelaide', freq='40S')

Display DateTimeIndex −

print("DateTimeIndex...\n", datetimeindex)

Convert DateTimeIndex to Series. Use the "tz_convert()" and set it to "None" to exclude the TimeZone −

print("\nDateTimeIndex to series excluding the TimeZone...\n",
datetimeindex.tz_convert(None).to_series())

Example

Following is the code −

import pandas as pd

# DatetimeIndex with period 5 and frequency as S i.e. seconds
# timezone is Australia/Adelaide
datetimeindex = pd.date_range('2021-10-18 07:20:32.261811624', periods=5,
tz='Australia/Adelaide', freq='40S')

# display DateTimeIndex
print("DateTimeIndex...\n", datetimeindex)

# display DateTimeIndex frequency
print("DateTimeIndex frequency...\n", datetimeindex.freq)

# Convert DateTimeIndex to Series
# Use the "tz_convert()" and set it to "None" to exclude the TimeZone
print("\nDateTimeIndex to series excluding the TimeZone...\n",
datetimeindex.tz_convert(None).to_series())

Output

This will produce the following code −

DateTimeIndex...
DatetimeIndex(['2021-10-18 07:20:32.261811624+10:30',
'2021-10-18 07:21:12.261811624+10:30',
'2021-10-18 07:21:52.261811624+10:30',
'2021-10-18 07:22:32.261811624+10:30',
'2021-10-18 07:23:12.261811624+10:30'],
dtype='datetime64[ns, Australia/Adelaide]', freq='40S')
DateTimeIndex frequency...
<40 * Seconds>

DateTimeIndex to series excluding the TimeZone...
2021-10-17 20:50:32.261811624 2021-10-17 20:50:32.261811624
2021-10-17 20:51:12.261811624 2021-10-17 20:51:12.261811624
2021-10-17 20:51:52.261811624 2021-10-17 20:51:52.261811624
2021-10-17 20:52:32.261811624 2021-10-17 20:52:32.261811624
2021-10-17 20:53:12.261811624 2021-10-17 20:53:12.261811624
Freq: 40S, dtype: datetime64[ns]