Python | Pandas DatetimeIndex.strftime()

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. Python3

# 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. Python3

# 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. Python3

# 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. Python3

# 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.