Series.dt can be used to access series values as datetimelike and return multiple properties. Series.dt.is_quarter_end Pandas Series.dt.is_quarter_end returns a boolean value indicating whether the date is the last day quarter.
Syntax: Series.dt.is_quarter_end
Parameter: None
Returns: numpy array
Example # 1: Use the Series.dt.is_quarter_end attribute to check if whether the dates in the underlying data of this series object are the last day of the quarter.
| |
Output: 
We will now use the Series.dt.is_quarter_end attribute to check if the dates in a given series object are the last day of the quarter or not.
| < code class = "comments"> # check if the dates are up to date |
Exit:
As we can see in the output, the Series. dt.is_quarter_end successfully accessed and returned boolean values indicating whether the dates are the last day of the quarter or not.
Example # 2: Use the Series attribute .dt.is_quarter_end to check if the dates in the underlying data of this series object are the last day of the quarter.
< p>
# import pandas as pd
import pandas as pd
# Create series
sr = pd.Series (pd.date_range ( `2012-1 -1 00: 00` ,
periods = 5 , freq = `Q` ))
# Create index
idx = [ ` Day 1` , `Day 2` , `Day 3` , ` Day 4` , `Day 5` ]
# set index
sr.index = idx
# Print series
print (sr)
Output:
We will now use the Series.dt.is_quarter_end attribute to check if the dates are in this object of the series last day quarters alright or not.
| |
Output:
As we can see in the output, the Series.dt.is_quarter_end attribute successfully accessed and returned boolean values indicating whether the dates are the last day of the quarter or not.
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