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.
import pandas as pd
ts = pd.Timestamp( 2016 , 3 , 31 , 12 )
print (ts)
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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.
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.
import pandas as pd
ts = pd.Timestamp(year = 2009 , month = 5 , day = 31 ,
hour = 4 , tz = 'Europe/Berlin' )
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.
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.