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.week 

Parameter : None 

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

# 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 = 'M'))

# 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.week attribute to return the week ordinal of the year in the underlying data of the given Series object.

Python3

# return the week ordinal
# of the year
result = sr.dt.week

# print the result
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.