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.weekofyear attribute return an Index object containing the ordinal value of week of each period element for the given PeriodIndex object.
Syntax : PeriodIndex.weekofyear
Parameters : None
Return : Index object
Example #1: Use PeriodIndex.weekofyear attribute to find out the ordinal value of week of each period element contained 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 ='2004-11-21 8:45:29', freq ='D') # Print the PeriodIndex object print(pidx) |
Output :
Now we will use the PeriodIndex.weekofyear attribute to find out the week’s ordinal value in the year for the given PeriodIndex object.
# return the week's ordinal value in the year pidx.weekofyear |
Output :
As we can see in the output, the PeriodIndex.weekofyear attribute has returned an Index object containing the ordinal value of the week for each period element contained in the given PeriodIndex object.
Example #2: Use PeriodIndex.weekofyear attribute to find out the ordinal value of week of each period element contained in the given PeriodIndex object.
# importing pandas as pd import pandas as pd # Create the PeriodIndex object pidx = pd.PeriodIndex(start ='2016-2-12 11:12:02', end ='2016-09-12 11:32:12', freq ='M') # Print the PeriodIndex object print(pidx) |
Output :
Now we will use the PeriodIndex.weekofyear attribute to find out the week’s ordinal value in the year for the given PeriodIndex object.
# return the week's ordinal value pidx.weekofyear |
Output :
As we can see in the output, the PeriodIndex.weekofyear attribute has returned an Index object containing the ordinal value of the week for each period element contained in the given PeriodIndex object.
