How to Extract Hour from DateTime Object in Pandas Series
To extract the hour value from the DateTime object in the Pandas Series we use the dt.hour attribute of the Pandas library in Python.
Let us understand it better with an example:
Example:
Use the Series.dt.hour attribute to return the hour 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 :
Now we will use the Series.dt.hour attribute to return the hour of the datetime in the underlying data of the given Series object.
Python3
# return the hour result = sr.dt.hour # print the result print (result) |
Output :
As we can see in the output, the Series.dt.hour attribute has successfully accessed and returned the hour of the DateTime in the underlying data of the given series object.
Pandas Series dt.hour | Extract Hour Part from Time Stamp
Pandas dt.hour attribute returns a NumPy array containing the hour 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.hour print (result) |
Output