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Python | Pandas Series.dt.quarter

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Series.dt can be used to access series values ​​as datetimelike and return multiple properties. Series.dt.quarter Pandas Series.dt.quarter returns a quarter of a date in the underlying data based on a date and time in this series object.

Syntax: Series.dt.quarter

Parameter: None

Returns: numpy array

Example # 1: Use the Series.dt.quarter attribute to return a quarter of the date in the underlying data of this Series object.

# import pandas as pd

import pandas as pd

  
# Create series

sr = pd.Series ([ ’ 2012-10-21 09:30’ , ’2019-7-18 12:30’ , ’2008-02-2 10:30’ ,

  ’2010-4-22 09: 25’ , ’ 2019 -11-8 02: 22’ ])

 
# Create index

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

 
# set index

sr.index = idx

 
# Convert base data to date and time

sr = pd.to_datetime (sr)

 
# Print series

print (sr)

Output:

Now we will use the Series.dt attribute .quarter to return the quarter date in the data based on the date and time in the given series object.

# return the quarter of the date

result = sr.dt.quarter

 
# print result

print (result)

Output:

As we can see from the output, the attribute Series.dt.quarter successfully accessed and returned a quarter date in the underlying data of this series object.

Example # 2: Use the Series attribute .dt.quarter to return the quarter date in the underlying data of this Series object.

# import pandas as pd

import pandas as pd

 
# Create a series

sr = pd.Series (pd.date_range ( ’ 2012-12-12 12: 12’

periods = 5 , freq = ’M’ ))

 
# 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.quarter attribute to return a quarter date in the data to based on the date and time in the given series object.

# return the quarter of the date

result = sr.dt.quarter

  
# print the result

print (result)

Output:

As we can see from the output, the Series.dt.quarter attribute successfully accessed and returned a quarter date in the underlying data this series object.

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