Python | Pandas Series.dt.week
Series.dt can be used to access the values of the series as datetimelike and return several properties. Pandas Series.dt.week attribute return a numpy array containing the week ordinal of the year in the underlying data of the given series object.
Syntax: Series.dt.week
Parameter : None
Returns : numpy array
Example #1: Use Series.dt.week attribute to return the week ordinal of the year in the underlying data of the given Series object.
Выход :
Now we will use Series.dt.week attribute to return the week ordinal of the year in the underlying data of the given Series object.
# return the week ordinal# of the yearresult = sr.dt.week # print the resultprint(result) |
Выход :
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.
Example #2 : Use Series.dt.week attribute to return the week ordinal of the year in the underlying data of the given Series object.
# importing pandas as pdimport pandas as pd # Creating the Seriessr = pd.Series(pd.date_range("2012-12-12 12:12", periods = 5, freq = "M")) # Creating the indexidx = ["Day 1", "Day 2", "Day 3", "Day 4", "Day 5"] # set the indexsr.index = idx # Print the seriesprint(sr) |
Выход :
Now we will use Series.dt.week attribute to return the week ordinal of the year in the underlying data of the given Series object.
# return the week ordinal# of the yearresult = sr.dt.week # print the resultprint(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.
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