Pandas Series dt.days_in_month | Get Total Number of Days in Month in Pandas

The Pandas dt.days_in_month attribute returns the total number of days in the month for the given Series object.

Example

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.days_in_month
print(result)

Output :

Syntax

Syntax: Series.dt.days_in_month 

Parameter: None 

Returns: Series with integers indicating the total number of days in the month

How to get Total Number of Days in the Month in Pandas Series

To get the total number of days in a month for a date in the Pandas Series we use the Series.dt.days_in_month attribute of the Pandas library.

Let us understand it better with an example:

Example:

Use the Series.dt.days_in_month attribute to find the total number of days in the month of the given date in the 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 the dt.days_in_month 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.days_in_month

# print the result
print(result)

Output :

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