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Pandas Series dt.minute | Extract Minute from DateTime Series in Pandas

Last Updated : 07 Feb, 2024
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Pandas Series.dt.minute attribute returns a NumPy array containing the minutes of the DateTime in the underlying data of the given series object.

Example

Python3




import pandas as pd
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'])
idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5']
sr.index = idx
sr = pd.to_datetime(sr)
result = sr.dt.minute
print(result)


Output :

dt.minute output

Syntax

Syntax: Series.dt.minuteĀ 

Parameter: NoneĀ 

Returns: NumPy array containing minutes

How to Extract the Minute from a DateTime in Pandas Series

To extract the minutes from a DateTime object in the Pandas Series we use the dt.minute attribute of the Pandas library in Python.

Let us understand it better with an example:

Example:

Use the Series.dt.minute attribute to return the minutes of the DateTime in the underlying data of the given Series object.

Python3




# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series(pd.date_range('2012-12-12 12:12',
                       periods = 5, freq = 'H'))
  
# 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 :

created datetime series

Now we will use the dt.minute attribute to return the minutes of the DateTime in the underlying data of the given Series object.

Python3




# return the minutes
result = sr.dt.minute
  
# print the result
print(result)


Output :

minutes extracted from DateTime Series

As we can see in the output, the dt.minute attribute has successfully accessed and returned the minutes of the DateTime in the underlying data of the given series object.



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