Pandas Series dt.daysinmonth | Get Number of Days in Month in Pandas Series
The dt.daysinmonth attribute returns the number of days in the month for the given DateTime series object.
Example
Python3
import pandas as pd
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' ])
idx = [ 'Day 1' , 'Day 2' , 'Day 3' , 'Day 4' , 'Day 5' ]
sr.index = idx
sr = pd.to_datetime(sr)
result = sr.dt.daysinmonth
print (result)
|
Output :
Syntax
Syntax: Series.dt.daysinmonth
Parameter: None
Returns: Series of  integers representing days in a month
How to Get the Number of Days in a Month in Pandas Series
To get the number of days in a month in the Pandas Series DateTime object, we use the dt.daysinmonth attribute of the Pandas library in Python.
Let us understand it with an example:
Example:
Use the dt.daysinmonth attribute to find the number of days in the month of the given date in the series object.
Python3
import pandas as pd
sr = pd.Series(pd.date_range( '2012-12-31 00:00' , periods = 5 , freq = 'D' ))
idx = [ 'Day 1' , 'Day 2' , 'Day 3' , 'Day 4' , 'Day 5' ]
sr.index = idx
print (sr)
|
Output :
Now we will use dt.daysinmonth attribute to find the number of days in the month for the given date.
Example 3
Python3
result = sr.dt.daysinmonth
print (result)
|
Output :
As we can see in the output, the dt.daysinmonth attribute has successfully accessed and returned the number of days in the month for the given date.
Last Updated :
08 Feb, 2024
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