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 Timestamp.is_quarter_end
attribute return a boolean value. It return True
if the date in the given Timestamp object is the quarter end else it return False
.
Syntax : Timestamp.is_quarter_end
Parameters : None
Return : boolean
Example #1: Use Timestamp.is_quarter_end
attribute to check if the date in the given Timestamp object is the quarter end or not.
# importing pandas as pd import pandas as pd # Create the Timestamp object ts = pd.Timestamp( 2016 , 3 , 31 , 12 ) # Print the Timestamp object print (ts) |
Output :
Now we will use the Timestamp.is_quarter_end
attribute to check if the date in the ts object is the quarter end or not.
# check if the date is quarter end or not ts.is_quarter_end |
Output :
As we can see in the output, the Timestamp.is_quarter_end
attribute has returned True
indicating the date in the given Timestamp object is quarter end
Example #2: Use Timestamp.is_quarter_end
attribute to check if the date in the given Timestamp object is the quarter end or not.
# importing pandas as pd import pandas as pd # Create the Timestamp object ts = pd.Timestamp(year = 2009 , month = 5 , day = 31 , hour = 4 , tz = 'Europe/Berlin' ) # Print the Timestamp object print (ts) |
Output :
Now we will use the Timestamp.is_quarter_end
attribute to check if the date in the ts object is the quarter end or not.
# check if the date is quarter end or not ts.is_quarter_end |
Output :
As we can see in the output, the Timestamp.is_quarter_end
attribute has returned False
indicating the date in the given Timestamp object is not the quarter end.
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