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Python | Pandas DatetimeIndex.is_leap_year

DatetimeIndex.is_leap_year Pandas DatetimeIndex.is_leap_year returns a boolean indicator if the date is in a leap year. Leap year — this is a year with 366 days (instead of 365), including February 29 as an intermediate day. Leap years — these are years in multiples of four, except for years that are multiples of 100, but not 400.

Syntax: DatetimeIndex.is_leap_year

Returns : numpy array containing logical values.

Example # 1: Use the DatetimeIndex.is_leap_year attribute to check if dates in a DatetimeIndex object leap year.

# import pandas as pd

import pandas as pd

 
# Create DatetimeIndex

didx = pd .DatetimeIndex ([ ’2014-01-01’ , ’ 2008 -12-31’ , ’2017-03-31’ , ’ 2000-12-31’ ])

 
# Print DatetimeIndex

print (didx)

Output:

Now we want to find out if the dates contained in this DatetimeIndex are leap years or not.

# determine if dates are in leap years
didx.is_leap_year

Output:
< br /> As we can see in the output, the function returned an empty array containing boolean values ​​for each record of the DatetimeIndex object.  True values ​​indicate that the corresponding date is in a leap year, and False values ​​indicate that the corresponding date is not in a leap year.

Example # 2: Use the DatetimeIndex.is_leap_year attribute to check if the dates in the DatetimeIndex are in a leap year.

# import pandas as pd

import pandas as pd

 
# Create DatetimeIndex

didx = pd.date_range ( "2008-12-30" periods = 5 , freq = ’Q’ )

 
# Print DatetimeIndex

print (didx)

Output:

Now we want to find out if the dates contained in given DatetimeIndex object, leap year or not.

# determine if dates are in a leap year
didx.is_leap_year

Output:

As we can see in the output, the function returned n a stub array containing the boolean values ​​for each entry in the DatetimeIndex object.  True values ​​indicate that the corresponding date is in a leap year, and False values ​​indicate that the corresponding date is not in a leap year.

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