Series.dt can be used to access the values of the series as datetimelike and return several properties. Pandas Series.dt.to_period() function cast the underlying data of the given Series object to PeriodArray/Index at a particular frequency.
Syntax: Series.dt.to_period(*args, **kwargs)
Parameter :
freq : string or Offset, optional
Returns : PeriodArray/Index
Example #1: Use Series.dt.to_period() function to cast the underlying data of the given series object to Index at Weekly frequency.
Python3
# importing pandas as pdimport pandas as pd# Creating the Seriessr = pd.Series(['2012-12-31', '2019-1-1 12:30', '2008-02-2 10:30', '2010-1-1 09:25', '2019-12-31 00:00'])# Creating the indexidx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5']# set the indexsr.index = idx# Convert the underlying data to datetime sr = pd.to_datetime(sr)# Print the seriesprint(sr) |
Output :
Now we will use Series.dt.to_period() function to cast the underlying data of the given series object to Index at Weekly frequency.
Python3
# cast to target frequencyresult = sr.dt.to_period(freq = 'W') # print the resultprint(result) |
Output :
As we can see in the output, the Series.dt.to_period() function has successfully cast the data to the target frequency.
Example #2 : Use Series.dt.to_period() function to cast the underlying data of the given series object to Index at two year frequency.
Python3
# importing pandas as pdimport pandas as pd# Creating the Seriessr = pd.Series(pd.date_range('2012-12-31 00:00', periods = 5, freq = 'D', tz = 'US / Central'))# Creating the indexidx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5']# set the indexsr.index = idx# Print the seriesprint(sr) |
Output :
Now we will use Series.dt.to_period() function to cast the underlying data of the given series object to Index at two year frequency.
Python3
# cast to target frequencyresult = sr.dt.to_period(freq = '2Y') # print the resultprint(result) |
Output :
As we can see in the output, the Series.dt.to_period() function has successfully cast the data to the target frequency.
