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 Period.week attribute returns an integer value which represents the week number in which the given period lies.
Syntax : Period.week
Parameters : None
Return : week of the year
Example #1: Use Period.week attribute to find out the week in which the given period object would lie.
# importing pandas as pd import pandas as pd
# Create the Period object prd = pd.Period(freq ='S', year = 2000, month = 2, day = 22,
hour = 8, minute = 21, second = 24)
# Print the Period object print(prd)
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Output :
Now we will use the Period.week attribute to find the week in which prd object lies.
# return the week value prd.week |
Output :
As we can see in the output, the Period.week attribute has returned 8 indicating the following period object lies in the 8th week of the given year.
Example #2: Use Period.week attribute to find out the week in which the given period object would lie.
# importing pandas as pd import pandas as pd
# Create the Period object prd = pd.Period(freq ='S', year = 2006, month = 10,
hour = 15, minute = 49, second = 17)
# Print the object print(prd)
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Output :
Now we will use the Period.week attribute to find the week in which prd object lies.
# return the week value prd.week |
Output :
As we can see in the output, the Period.week attribute has returned 39 indicating the following period object lies in the 39th week of the given year.