Python | Pandas Series.dt.week

Series.dt can be used to access series values ​​as datetimelike and return multiple properties. Series.dt.week Pandas Series.dt.week returns an empty array containing the ordinal of the week in the year in base data of this series object.

Syntax: Series.dt.week

Parameter: None

Returns: numpy array

Example # 1: Use the Series.dt.week attribute to return the ordinal week of the year in the underlying data of this Series object.

# import pandas as pd

import pandas as pd

 
# Create 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` ])

  
# Create index

idx = [ `Day 1` , `Day 2` , ` Day 3` , `Day 4` , ` Day 5 ` ]

  
#est Browse index

sr.index = idx

 
# Convert baseline data to date and time

sr = pd.to_datetime (sr)

 
# Print series

print (sr)

Output:

Now we we will use the Series.dt.week attribute to return the ordinal week of the year in the underlying data of this Series object.

# return the order week number
# of the year

result = sr.dt.week

  
# print the result

print (result)

Output:

As we can see from the output, the Series.dt.week attribute successfully accessed and returned an ordinal the week number of the year in the underlying data of this series object.

Example # 2: Use the Series.dt.week attribute to return the ordinal week of the year in base data of this Series object.

# im pandas port as pd

import pandas as pd

 
# Create series

sr = pd.Series (pd.date_range ( `2012-12-12 12 : 12` , periods = 5 , freq = `M` ))

 
# Create index

idx = [ `Day 1` , `Day 2` , `Day 3` , ` Day 4` , `Day 5` ]

 
# set index

sr.index = idx

 
# Print series

print (sr)

Output:

Now we will use the Series.dt attribute .week to return the ordinal of the week of the year in the underlying data of this Series object.

# return the ordinal number of the week
#years

result = sr.dt.week

  
# print result

print (result)

Output:

As we can see from the output, the Series.dt.week attribute successfully accessed and returned the week ordinal of the year in the underlying data of this series object.