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
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)
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Output :
Syntax
Syntax: Series.dt.minute
Parameter: None
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.
# 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)
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Output :
Now we will use the dt.minute attribute to return the minutes of the DateTime in the underlying data of the given Series object.
# return the minutes result = sr.dt.minute
# print the result print (result)
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Output :
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.