Series.dt
can be used to access the values of the series as datetimelike and return several properties. Pandas Series.dt.minute
attribute return a numpy array containing the minutes of the datetime in the underlying data of the given series object.
Syntax: Series.dt.minute
Parameter : None
Returns : numpy array
Example #1: Use 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([ '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' ]) # Creating the index idx = [ 'Day 1' , 'Day 2' , 'Day 3' , 'Day 4' , 'Day 5' ] # set the index sr.index = idx # Convert the underlying data to datetime sr = pd.to_datetime(sr) # Print the series print (sr) |
Output :
Now we will use Series.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) |
Output :
As we can see in the output, the Series.dt.minute
attribute has successfully accessed and returned the minutes of the datetime in the underlying data of the given series object.
Example #2 : Use 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) |
Output :
Now we will use Series.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) |
Output :
As we can see in the output, the Series.dt.minute
attribute has successfully accessed and returned the minutes of the datetime in the underlying data of the given series object.
Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.
To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.