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.
