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 DatetimeIndex.quarter attribute outputs the quarter of the date for each entries in the DatetimeIndex object.
Syntax: DatetimeIndex.quarter
Return: Index object
Example #1: Use DatetimeIndex.quarter attribute to find the quarter of the date for each entries in the DatetimeIndex object.
# importing pandas as pd import pandas as pd # Create the DatetimeIndex # Here 'M' represents Monthly frequency didx = pd.DatetimeIndex(start ='2014-08-01 10:05:45', freq ='M', periods = 5, tz ='Asia/Calcutta') # Print the DatetimeIndex print(didx) |
Output :
Now we want to find quarter of the date for each entries in the DatetimeIndex object.
# find the quarter of date didx.quarter |
Output :
As we can see in the output, the function has returned an Index object containing the quarter value of the date for each entry of the DatetimeIndex object.
Example #2: Use DatetimeIndex.quarter attribute to find the quarter of the date for each entries in the DatetimeIndex object.
# importing pandas as pd import pandas as pd # Create the DatetimeIndex # Here 'Q' represents Quarterly frequency didx = pd.DatetimeIndex(start ='2000-01-10 06:30', freq ='Q', periods = 5, tz ='Asia/Calcutta') # Print the DatetimeIndex print(didx) |
Output :
Now we want to find quarter of the date for each entries in the DatetimeIndex object.
# find the quarter of date didx.quarter |
Output :
As we can see in the output, the function has returned an Index object containing the quarter value of the date for each entry of the DatetimeIndex object.
