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.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 quarter
Example #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) |
Output :
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 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) |
Output :
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 Period.quarter
attribute has returned 4 indicating that the given date in the prd object falls in the fourth quarter of the year.