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Python | Pandas DatetimeIndex.is_leap_year

Last Updated : 24 Dec, 2018
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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.is_leap_year attribute return a boolean indicator if the date belongs to a leap year. A leap year is a year, which has 366 days (instead of 365) including 29th of February as an intercalary day. Leap years are years which are multiples of four with the exception of years divisible by 100 but not by 400.

Syntax: DatetimeIndex.is_leap_year

Returns: numpy array containing logical values.

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




# importing pandas as pd
import pandas as pd
  
# Create the DatetimeIndex
didx = pd.DatetimeIndex(['2014-01-01', '2008-12-31', '2017-03-31', '2000-12-31'])
  
# Print the DatetimeIndex
print(didx)


Output :

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




# find if the dates belong to leap year
didx.is_leap_year


Output :

As we can see in the output, the function has returned a numpy array containing logical values for each entry of the DatetimeIndex object. True values indicate the corresponding date belongs to a leap year and False value indicate the corresponding date does not belongs to a leap year.
 
Example #2: Use DatetimeIndex.is_leap_year attribute to check if the dates present in the DatetimeIndex object belongs to a leap year.




# importing pandas as pd
import pandas as pd
  
# Create the DatetimeIndex
didx = pd.date_range("2008-12-30", periods = 5, freq ='Q')
  
# Print the DatetimeIndex
print(didx)


Output :

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




# find if the dates belong to leap year
didx.is_leap_year


Output :

As we can see in the output, the function has returned a numpy array containing logical values for each entry of the DatetimeIndex object. True values indicate the corresponding date belongs to a leap year and False value indicate the corresponding date does not belongs to a leap year.



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