Python | Pandas Series.dt.to_pydatetime

Series.dt can be used to access the values of the series as datetimelike and return several properties. Pandas Series.dt.to_pydatetime() function return the data as an array of native Python datetime objects. Timezone information is retained if present.

Syntax: Series.dt.to_pydatetime()

Parameter : None



Returns : numpy.ndarray

Example #1: Use Series.dt.to_pydatetime() function to return the given series object as an array of native python datetime object.

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# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = 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 index
idx = ['Day 1', 'Day 2', 'Day 3', 'Day 4', 'Day 5']
  
# set the index
sr.index = idx
  
# Convert the underlying data to datetime 
sr = pd.to_datetime(sr)
  
# Print the series
print(sr)

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Output :

Now we will use Series.dt.to_pydatetime() function to return the data as an array of native Python datetime objects.

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# return the series data as a 
# native python datetime data
result = sr.dt.to_pydatetime() 
  
# print the result
print(result)

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Output :

As we can see in the output, the Series.dt.to_pydatetime() function has successfully returned the underlying data of the given series object as an array of native python datetime data.

Example #2 : Use Series.dt.to_pydatetime() function to return the given series object as an array of native python datetime object.

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# importing pandas as pd
import pandas as pd
  
# Creating the Series
sr = pd.Series(pd.date_range('2012-12-31 00:00', periods = 5, freq = 'D',
                            tz = 'US / Central'))
  
# 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)

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Output :


Now we will use Series.dt.to_pydatetime() function to return the data as an array of native Python datetime objects.

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# return the series data as a 
# native python datetime data
result = sr.dt.to_pydatetime() 
  
# print the result
print(result)

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Output :

As we can see in the output, the Series.dt.to_pydatetime() function has successfully returned the underlying data of the given series object as an array of native python datetime data.



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