Pandas Series dt.minute | Extract Minute from DateTime Series in Pandas
Last Updated :
07 Feb, 2024
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 :
Syntax
Syntax: Series.dt.minuteÂ
Parameter: NoneÂ
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
import pandas as pd
sr = pd.Series(pd.date_range( '2012-12-12 12:12' ,
periods = 5 , freq = 'H' ))
idx = [ 'Day 1' , 'Day 2' , 'Day 3' , 'Day 4' , 'Day 5' ]
sr.index = idx
print (sr)
|
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.
Python3
result = sr.dt.minute
print (result)
|
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.
Like Article
Suggest improvement
Share your thoughts in the comments
Please Login to comment...