Pandas Series dt.quarter | Find Quarter from DateTime Object
Pandas dt.quarter attribute returns the quarter of the date in the underlying DateTime based data in 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' ]
sr.index = idx
sr = pd.to_datetime(sr)
result = sr.dt.quarter
print (result)
|
Output
Syntax
Syntax: Series.dt.quarterÂ
Parameter : NoneÂ
Returns: NumPy array containing quarter value
How to Get Quarter Value from DateTime Object in Pandas Series
To get the quarter value from the DateTime object in the Pandas series we use the dt.quarter attribute of the Pandas library in Python.
Let us understand it better with an example:
Example:
Use the dt.quarter attribute to return the quarter of the date in the underlying data of the given Series object.
Python3
import pandas as pd
sr = pd.Series(pd.date_range( '2012-12-12 12:12' ,
periods = 5 , freq = 'M' ))
idx = [ 'Day 1' , 'Day 2' , 'Day 3' , 'Day 4' , 'Day 5' ]
sr.index = idx
print (sr)
|
Output :
Now we will use the Series.dt.quarter attribute to return the quarter of the date in the DateTime based data in the given series object.
Python3
result = sr.dt.quarter
print (result)
|
Output :
As we can see in the output, the Pandas dt.quarter attribute has successfully accessed and returned the quarter of the date in the underlying data of the given series object.
Last Updated :
07 Feb, 2024
Like Article
Save Article
Share your thoughts in the comments
Please Login to comment...