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
Python3
Output :
Now we will use the
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Period.quarter attribute return an integer value. The returned value represents the value of the quarter in the given period object.
Syntax : Period.quarter Parameters : None Return : integer value representing the value of quarterExample #1: Use
Period.quarter attribute to find the value of quarter in 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.quarter attribute to find out value of quarter in prd object.
# return value of quarter
prd.quarter
As we can see in the output, the Period.quarter attribute has returned 1 indicating that the given date in the prd object falls in the first quarter of the year.
Example #2: Use Period.quarter attribute to find the value of quarter in 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.quarter attribute to find out value of quarter in prd object.
# return value of quarter
prd.quarter
Output :
As we can see in the output, the
As we can see in the output, the Period.quarter attribute has returned 4 indicating that the given date in the prd object falls in the fourth quarter of the year.