Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier.
Pandas PeriodIndex.quarter attribute return an Index object containing the quarter of the date for each period in the given PeriodIndex object.
Syntax : PeriodIndex.quarter
Parameters : None
Return : Index object
Example #1: Use PeriodIndex.quarter attribute to find out the quarter of the date for each period in the given PeriodIndex object.
# importing pandas as pd import pandas as pd   # Create the PeriodIndex object pidx = pd.PeriodIndex(start ='2003-4-21 08:45 ',               end ='2003-12-21 8:55', freq ='Q')   # Print the PeriodIndex object print(pidx) |
Output :
Now we will use the PeriodIndex.quarter attribute to find out the quarter of the date for each period in pidx.
# return the quarter of each date pidx.quarter |
Output :
As we can see in the output, the PeriodIndex.quarter attribute has returned an Index object containing the quarter value for the given PeriodIndex object.
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Example #2: Use PeriodIndex.quarter attribute to find out the quarter of the date for each period in the given PeriodIndex object.
# importing pandas as pd import pandas as pd   # Create the PeriodIndex object pidx = pd.PeriodIndex(start ='2016-8-12 11:32',             end ='2017-04-05 11:55', freq ='M')   # Print the PeriodIndex object print(pidx) |
Output :
Now we will use the PeriodIndex.quarter attribute to find out the quarter of the date for each period in pidx.
# return the quarter of each date pidx.quarter |
Output :
As we can see in the output, the PeriodIndex.quarter attribute has returned an Index object containing the quarter value for the given PeriodIndex object.
