Pandas Series dt.month | Extract Month Part From DateTime Series

Pandas Series dt.day | Extract Day Part from DateTime Series

Last Updated : 06 Feb, 2024

Pandas dt.day attribute returns a NumPy array containing the day value of the DateTime in the underlying data of the given series object.

Example

Python3

import pandas as pd 
  
sr = pd.Series(['2012-10-21 09:30', '2019-7-18 12:30', '2008-02-2 10:30', 
                '2010-4-22 09:25', '2019-11-8 02:22']) 
idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5'] 
  
# set the index 
sr.index = idx 
sr = pd.to_datetime(sr) 
print(sr)

Output

output of dt.day attribute

Syntax

Syntax: Series.dt.day

Parameter : None

Returns: NumPy array containing day values

How to Extract Day From DateTime Series

To extract the day value from the DateTime Series we use the dt.day attribute of the Pandas library in Python.

Let us understand it better with an example:

Example:

Use the Series.dt.day attribute to return the day of the DateTime in the underlying data of the given Series object.

Python3

# importing pandas as pd 
import pandas as pd 
  
# Creating the Series 
sr = pd.Series(pd.date_range('2012-12-12 12:12',  
                       periods = 5, freq = 'H')) 
  
# 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 :

time series created

Now we will use the Series.dt.day attribute to return the day of the datetime in the underlying data of the given Series object.

Python3

# return the day 
result = sr.dt.day 
  
# print the result 
print(result)

Output :

As we can see in the output, the Series.dt.day attribute has successfully accessed and returned the day of the DateTime in the underlying data of the given series object.

Pandas Series dt.month | Extract Month Part From DateTime Series

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Shubham__Ranjan

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