Python | Pandas Series.dt.is_quarter_end

Michael Zippo 18.07.2021

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Series.dt can be used to access series values ‚Äã‚Äãas 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.

# import pandas as pd

import pandas as pd

# Create series

sr = pd.Serie s ([ ’2012-3-31’ , ’ 2019- 7-18 12: 30’ , ’2008-02-2 10: 30’ ,

’2010-4-22 09:25’ , ’2019-12-31 00:00’ ])

# Create index

idx = [ ’Day 1’ , ’Day 2’ , ’Day 3’ , ’ Day 4’ , ’Day 5’ ]

# set index

sr.index = idx

# Convert baseline data to date and time

sr = pd.to_datetime ( sr)

# Print series

print (sr)

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.

# check if the dates are up to date
# day of the quarter

result = sr.dt.is_quarter_end

# print the result

print (result)

Exit:

As we can see in the output, the Series. dt.is_quarter_end successfully accessed and returned boolean values ‚Äã‚Äãindicating 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.

# check if the dates are up to date
# day of the quarter

result = sr.dt.is_quarter_end

# print result

print (result)

Output:

As we can see in the output, the Series.dt.is_quarter_end attribute successfully accessed and returned boolean values ‚Äã‚Äãindicating whether the dates are the last day of the quarter or not.

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Olivia Emmerson

Milan | 2023-02-02

http Python module is always a bit confusing 😭 Python | Pandas Series.dt.is_quarter_end is not the only problem I encountered. Checked yesterday, it works!

Anna Krasiko

California | 2023-02-02

Thanks for explaining! I was stuck with Python | Pandas Series.dt.is_quarter_end for some hours, finally got it done 🤗. I am just not quite sure it is the best method

Julia Chamberlet

Tallinn | 2023-02-02

I was preparing for my coding interview, thanks for clarifying this - Python | Pandas Series.dt.is_quarter_end in Python is not the simplest one. I am just not quite sure it is the best method