Pandas Series dt.is_quarter_start | Check if a Date is First day of Quarter
Pandas dt.is_quarter_start attribute returns a boolean value indicating whether the date is the first day of a quarter.
Example:
Python3
import pandas as pd sr = pd.Series([ '2012-4-1' , '2019-7-18 12:30' , '2008-02-2 10:30' , '2010-4-22 09:25' , '2019-1-1 00:00' ]) idx = [ 'Day 1' , 'Day 2' , 'Day 3' , 'Day 4' , 'Day 5' ] sr.index = idx sr = pd.to_datetime(sr) result = sr.dt.is_quarter_start print (result) |
Output :
Syntax
Syntax: Series.dt.is_quarter_start
Parameter: None
Returns: Series with boolean values
How to Check if Date is First in it’s Quarter in Pandas Series
To check if a Date is the first date in its respective quarter in the Pandas Series, we use the dt.is_quarter_start attribute of the Pandas Library in Python.
Let us understand it better with an example:
Example
Use the Series.dt.is_quarter_start attribute to check if the dates in the underlying data of the given series object are the first day of the quarter.
Python3
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series(pd.date_range( '2012-4-1 00:00' , periods = 5 , freq = 'W' )) # Creating the index idx = [ 'Day 1' , 'Day 2' , 'Day 3' , 'Day 4' , 'Day 5' ] # set the index sr.index = idx # Print the series print (sr) |
Output :
Now we will use the dt.is_quarter_start attribute to check if the dates in the given series object is the first day of the quarter or not.
Python3
# check if dates are the first # day of the quarter result = sr.dt.is_quarter_start # print the result print (result) |
Output :
As we can see in the output, the dt.is_quarter_start attribute has successfully accessed and returned boolean values indicating whether the dates are the first day of the quarter.