The dt.daysinmonth attribute returns the number of days in the month for the given DateTime 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.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.
# 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 dt.daysinmonth attribute to find the number of days in the month for the given date.
Example 3
# 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 dt.daysinmonth attribute has successfully accessed and returned the number of days in the month for the given date.