Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.
Pandas DatetimeIndex.strftime() function convert to Index using specified date_format. The function return an Index of formatted strings specified by date_format, which supports the same string format as the python standard library.
Syntax: DatetimeIndex.strftime(date_format)
Parameters :
date_format : Date format string (e.g. “%Y-%m-%d”).Return : Index of formatted strings
Example #1: Use DatetimeIndex.strftime() function to convert the given DatetimeIndex object to the specified format.
# importing pandas as pd import pandas as pd # Create the DatetimeIndex # Here 'Q' represents quarter end frequency didx = pd.DatetimeIndex(start ='2000-01-15 08:00', freq ='Q', periods = 4, tz ='Asia/Calcutta') # Print the DatetimeIndex print(didx) |
Output :
Now we want to convert the given DatetimeIndex object to ('%B %d, %Y, %r') format.
# change the datetime format. didx.strftime('% B % d, % Y, % r') |
Output :
As we can see in the output, the function has changed the format of the DatetimeIndex object to the desired format.
Example #2: Use DatetimeIndex.strftime() function to convert the given DatetimeIndex object to the specified format.
# importing pandas as pd import pandas as pd # Create the DatetimeIndex # Here 'MS' represents month start frequency didx = pd.date_range(pd.Timestamp("2000-01-15 08:00"), periods = 5, freq ='MS') # Print the DatetimeIndex print(didx) |
Output :
Now we want to convert the given DatetimeIndex object to ('%B %Y, %r') format.
# change the datetime format. didx.strftime('% B % Y, % r') |
Output :
As we can see in the output, the function has changed the format of the DatetimeIndex object to the desired format.
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