Series.dt can be used to access the values of the series as datetimelike and return several properties. Pandas Series.dt.quarter attribute return the quarter of the date in the underlying datetime based data in the given series object.
Syntax: Series.dt.quarter
Parameter : None
Returns : numpy array
Example #1: Use Series.dt.quarter attribute to return the quarter of the date in the underlying data of the given Series object.
# importing pandas as pd import pandas as pd # Creating the Series 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']) # Creating the index idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5'] # set the index sr.index = idx # Convert the underlying data to datetime sr = pd.to_datetime(sr) # Print the series print(sr) |
Output :
Now we will use Series.dt.quarter attribute to return the quarter of the date in the datetime based data in the given series object.
# return the quarter of the date result = sr.dt.quarter # print the result print(result) |
Output :
As we can see in the output, the Series.dt.quarter attribute has successfully accessed and returned the quarter of the date in the underlying data of the given series object.
Example #2 : Use Series.dt.quarter attribute to return the quarter of the date in the underlying data of the given Series object.
# 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 = 'M')) # 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 Series.dt.quarter attribute to return the quarter of the date in the datetime based data in the given series object.
# return the quarter of the date result = sr.dt.quarter # print the result print(result) |
Output :
As we can see in the output, the Series.dt.quarter attribute has successfully accessed and returned the quarter of the date in the underlying data of the given series object.
