Pandas Series dt.week | Extract Week Number from DateTime Series
Pandas dt.week attribute returns a NumPy array containing the week ordinal of the year in the underlying data of the given DateTime 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.week
print (result)
|
Output
Syntax
Syntax: Series.dt.weekÂ
Parameter : NoneÂ
Returns: NumPy array containing week values
How to Extract Week From DateTime Series
To extract the week value from the DateTime series we use the Series.dt.week attribute of the Pandas library in Python.
Let us understand it better with an example:
Example:
Use the Series.dt.week attribute to return the week ordinal of the year 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 = 'M' ))
idx = [ 'Day 1' , 'Day 2' , 'Day 3' , 'Day 4' , 'Day 5' ]
sr.index = idx
print (sr)
|
Output :
Now we will use the Series.dt.week attribute to return the week ordinal of the year in the underlying data of the given Series object.
Python3
result = sr.dt.week
print (result)
|
Output :
As we can see in the output, the Series.dt.week attribute has successfully accessed and returned the week ordinal of the year in the underlying data of the given series object.
Last Updated :
06 Feb, 2024
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