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)
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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)
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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)
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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.