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.year attribute return an Index object containing the year value of each period element in the given PeriodIndex object.
Syntax : PeriodIndex.year
Parameters : None
Return : Index object
Example #1: Use PeriodIndex.year attribute to find out the year of the period for each element in the given PeriodIndex object.
# importing pandas as pd import pandas as pd # Create the PeriodIndex object pidx = pd.PeriodIndex(start ='2004-11-11 02:45:21 ', end ='2021-5-21 8:45:29', freq ='Y') # Print the PeriodIndex object print(pidx) |
Output :
Now we will use the PeriodIndex.year attribute to find out the year value of each period element in the given PeriodIndex object.
# return the year of each period pidx.year |
Output :
As we can see in the output, the PeriodIndex.year attribute has returned an Index object containing the year of period for each element in the given PeriodIndex object.
Example #2: Use PeriodIndex.year attribute to find out the year of the period for each element in the given PeriodIndex object.
# importing pandas as pd import pandas as pd # Create the PeriodIndex object pidx = pd.PeriodIndex(start ='2016-10-12 11:12:02', end ='2017-04-12 11:32:12', freq ='M') # Print the PeriodIndex object print(pidx) |
Output :
Now we will use the PeriodIndex.year attribute to find out the year value of each period element in the given PeriodIndex object.
# return the year of each period pidx.year |
Output :
As we can see in the output, the PeriodIndex.year attribute has returned an Index object containing the year of period for each element in the given PeriodIndex object.
