Series.dt can be used to access the values of the series as datetimelike and return several properties. Pandas Series.dt.daysinmonth attribute return the number of days in the month for the given series object.
Syntax: Series.dt.daysinmonth
Parameter : None
Returns : numpy array
Example #1: Use Series.dt.daysinmonth attribute to find the number of days in the month of the given date in series object.
# 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.daysinmonth attribute to find the number of days in the month for the given date.
# find the number of # days in the month result = sr.dt.daysinmonth   # print the result print(result) |
Output :
As we can see in the output, the Series.dt.daysinmonth attribute has successfully accessed and returned the number of days in the month for the given date.
Example #2 : Use Series.dt.daysinmonth attribute to find the number of days in the month of the given date in series object.
# 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.daysinmonth attribute to find the number of days in the month for the given date.
# find the number of # days in the month result = sr.dt.daysinmonth   # print the result print(result) |
Output :
As we can see in the output, the Series.dt.daysinmonth attribute has successfully accessed and returned the number of days in the month for the given date.
