Python Pandas - Create a DataFrame from DateTimeIndex ignoring the index

PythonServer Side ProgrammingProgramming

To create a DataFrame from DateTimeIndex ignoring the index, use the DateTimeIndex.to_frame() method. Set the parameter index to False to ignore the index.

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...
", datetimeindex)

Create a DataFrame from DateTimeIndex. The original index isn't set in the returned DataFrame using the 'False' parameter −

print("
DateTimeIndex to DataFrame...
", datetimeindex.to_frame(index=False))

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...
", datetimeindex) # display DateTimeIndex frequency print("
DateTimeIndex frequency...
", datetimeindex.freq) # Create a DataFrame from DateTimeIndex # The original index isn't set in the returned DataFrame using the 'False' parameter print("
DateTimeIndex to DataFrame...
", datetimeindex.to_frame(index=False))

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 DataFrame...
0
0 2021-10-18 07:20:32.261811624+10:30
1 2021-10-18 07:21:12.261811624+10:30
2 2021-10-18 07:21:52.261811624+10:30
3 2021-10-18 07:22:32.261811624+10:30
4 2021-10-18 07:23:12.261811624+10:30
raja
Updated on 19-Oct-2021 10:10:25

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