Python | Pandas Series.dt.daysinmonth

Series.dt can be used to access series values ​​as datetimelike and return multiple properties. Series.dt.daysinmonth Pandas Series.dt.daysinmonth returns the number of days in a month for a given series object.

Syntax: Series.dt.daysinmonth

Parameter: None

Returns: numpy array

Example # 1: Use the Series.dt.daysinmonth attribute to find the number of days in a month given date in the series object.

# import pandas as pd import pandas as pd   # Create a 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’ ])   # Create index idx = [ ’Day 1’ , ’ Day 2’ , ’Day 3’ , ’ Day 4’ , ’Day 5’ ]   # set index sr.index = idx    # Convert base data to date and time sr = pd.to_datetime (sr)   # Print series print (sr)

Output:

We will now use the Series.dt.daysinmonth attribute to find the number of days in a month for a given date.

# find number # days in a month result = sr.dt.daysinmonth   # print the result print (result)

Output:

As we can see from the output, the Series.dt.daysinmonth attribute successfully accessed and returned the number of days in the month for the given date.

Example # 2: Use the Series attribute .dt.daysinmonth to find the number of days in the month of a given date in a series object.

# import pandas as pd import pandas as pd < p>   # Create series sr = pd.Series (pd.date_range ( ’2012-12- 31 00:00’ , periods = 5 , freq = ’D’ ) )   # Create index idx = [ ’Day 1’ , ’Day 2’ , ’Day 3’ , ’ Day 4’ , ’Day 5’ ]   # set index sr.index = idx    # Print series print (sr)

Exit :

Now we will use the Series.dt.daysinmonth attribute to find the number of days in a month for a given date.

# find number # days in a month result = sr.dt.daysinmonth   # print result print (result)

Output:

How we can see from the output that the Series.dt.daysinmonth attribute successfully accessed and returned the number of days in the month for the given date.