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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.

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