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
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Output :
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Output :
As we can see in the output, the
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Output :
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Period.year attribute return an integer value representing the year the given period lies in.
Syntax : Period.year Parameters : None Return : yearExample #1: Use
Period.year attribute to find the year the period lies in for the given Period object.
# importing pandas as pd
import pandas as pd
# Create the Period object
prd = pd.Period(freq ='S', year = 2000, month = 2,
day = 21, hour = 8, minute = 21)
# Print the Period object
print(prd)
Now we will use the Period.year attribute to find the value of year
# return the year value
prd.year
As we can see in the output, the Period.year attribute has returned 2000 indicating that the given period lies in the year of 2000.
Example #2: Use Period.year attribute to find the year the period lies in for the given Period object.
# importing pandas as pd
import pandas as pd
# Create the Period object
prd = pd.Period(freq ='T', year = 2006, month = 10,
hour = 15, minute = 49)
# Print the Period object
print(prd)
Now we will use the Period.year attribute to find the value of year
# return the year
prd.year
Output :
As we can see in the output, the
As we can see in the output, the Period.year attribute has returned 2006 indicating that the given period lies in the year of 2006.