Python | Pandas Series.dt.is_leap_year Last Updated : 20 Mar, 2019 Summarize Comments Improve Suggest changes Share Like Article Like Report Series.dt can be used to access the values of the series as datetimelike and return several properties. Pandas Series.dt.is_leap_year attribute return a boolean indicator if the date belongs to a leap year. Syntax: Series.dt.is_leap_year Parameter : None Returns : numpy array Example #1: Use Series.dt.is_leap_year attribute to check if the dates in the underlying data of the given series object belongs to a leap year. Python3 # importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series(['2012-12-31', '2019-1-1 12:30', '2008-02-2 10:30', '2010-1-1 09:25', '2019-12-31 00:00']) # Creating the index idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5'] # set the index sr.index = idx # Convert the underlying data to datetime sr = pd.to_datetime(sr) # Print the series print(sr) Output : Now we will use Series.dt.is_leap_year attribute to check if the dates in the given series object belongs to a leap year. Python3 # check if dates given # belongs to a leap year. result = sr.dt.is_leap_year # print the result print(result) Output : As we can see in the output, the Series.dt.is_leap_year attribute has successfully accessed and returned boolean values indicating whether the dates in the given series object belongs to a leap year. Example #2 : Use Series.dt.is_leap_year attribute to check if the dates in the underlying data of the given series object belongs to a leap year. Python3 # importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series(pd.date_range('2012-12-31 00:00', periods = 5, freq = 'D')) # Creating the index idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5'] # set the index sr.index = idx # Print the series print(sr) Output : Now we will use Series.dt.is_leap_year attribute to check if the dates in the given series object belongs to a leap year. Python3 # check if dates given # belongs to a leap year. result = sr.dt.is_leap_year # print the result print(result) Output : As we can see in the output, the Series.dt.is_leap_year attribute has successfully accessed and returned boolean values indicating whether the dates in the given series object belongs to a leap year. Comment More infoAdvertise with us Next Article Python | Pandas Series.dt.is_leap_year S Shubham__Ranjan Follow Improve Article Tags : Pandas Python-pandas Python pandas-series-datetime AI-ML-DS With Python Similar Reads Python | Pandas Series.dt.is_year_end Series.dt can be used to access the values of the series as datetimelike and return several properties. Pandas Series.dt.is_year_end attribute return a boolean value Indicating whether the date is the last day of a year. Syntax: Series.dt.is_year_end Parameter : None Returns : numpy array Example #1 2 min read Python | Pandas Series.dt.is_year_start Series.dt can be used to access the values of the series as datetimelike and return several properties. Pandas Series.dt.is_year_start attribute return a boolean value Indicating whether the date is the first day of a year. Syntax: Series.dt.is_year_start Parameter : None Returns : numpy array Examp 2 min read Python | Pandas Timestamp.is_leap_year 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 Timestamp.is_leap_year attribute return a boolean value. It return True if the 2 min read Python | Pandas DatetimeIndex.is_leap_year 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 bel 2 min read Python | Pandas Timestamp.is_year_end 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 Timestamp.is_year_end attribute return a boolean value. It return True if the d 2 min read Like