Python Pandas - Return an Index of formatted strings specified by date format

To return an Index of formatted strings specified by date format, use the DateTimeIndex.strftime() method in Pandas.

At first, import the required libraries −

import pandas as pd

Create a DatetimeIndex with period 7 and frequency as D i.e. days −

datetimeindex = pd.date_range('2021-10-30 02:30:50', periods=7, tz='Australia/Adelaide', freq='2D')

Display DateTimeIndex −

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

Formatted −

print("\nFormat with different directives...\n",
datetimeindex.strftime('%b. %d, %Y was a %A'))

Example

Following is the code −

import pandas as pd

# DatetimeIndex with period 7 and frequency as D i.e. days
# The timezone is Australia/Adelaide
datetimeindex = pd.date_range('2021-10-30 02:30:50', periods=7, tz='Australia/Adelaide', freq='2D')

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

# display DateTimeIndex frequency
print("\nDateTimeIndex frequency...\n", datetimeindex.freq)
# display the result
print("\nFormat with different directives...\n",
datetimeindex.strftime('%b. %d, %Y was a %A'))

Output

This will produce the following code −

DateTimeIndex...
DatetimeIndex(['2021-10-30 02:30:50+10:30', '2021-11-01 02:30:50+10:30',
'2021-11-03 02:30:50+10:30', '2021-11-05 02:30:50+10:30',
'2021-11-07 02:30:50+10:30', '2021-11-09 02:30:50+10:30',
'2021-11-11 02:30:50+10:30'],
dtype='datetime64[ns, Australia/Adelaide]', freq='2D')

DateTimeIndex frequency...
<2 * Days>

Format with different directives...
Index(['Oct. 30, 2021 was a Saturday', 'Nov. 01, 2021 was a Monday',
'Nov. 03, 2021 was a Wednesday', 'Nov. 05, 2021 was a Friday',
'Nov. 07, 2021 was a Sunday', 'Nov. 09, 2021 was a Tuesday',
'Nov. 11, 2021 was a Thursday'],
dtype='object')

AmitDiwan

Updated on: 18-Oct-2021

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