Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas DatetimeIndex.to_pydatetime() function return DatetimeIndex as object ndarray of datetime.datetime objects. The function does not take any input value.

Syntax: DatetimeIndex.to_pydatetime() Parameters : None Return : ndarray

Example #1: Use DatetimeIndex.to_pydatetime() function to convert the DatetimeIndex as object ndarray of datetime.datetime objects.

# importing pandas as pd
import pandas as pd

# Create the DatetimeIndex
# Here 'S' represents secondly frequency 
didx = pd.DatetimeIndex(start ='2018-11-15 09:45:10', freq ='S', periods = 5)

# Print the DatetimeIndex
print(didx)

Output : Now we want to convert the DatetimeIndex to datetime.datetime objects.

# convert to datetime.datetime objects.
didx.to_pydatetime()

Output : As we can see in the output, the function has converted the DatetimeIndex object to python datetime.datetime object.   Example #2: Use DatetimeIndex.to_pydatetime() function to convert the DatetimeIndex as object ndarray of datetime.datetime objects.

# importing pandas as pd
import pandas as pd

# Create the DatetimeIndex
# Here 'M' represents monthly frequency 
didx = pd.DatetimeIndex(start ='2015-03-02', freq ='M', periods = 5)

# Print the DatetimeIndex
print(didx)

Output : Now we want to convert the DatetimeIndex to datetime.datetime objects.

# convert to datetime.datetime objects.
didx.to_pydatetime()

Output : As we can see in the output, the function has converted the DatetimeIndex object to python datetime.datetime object.