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 TimedeltaIndex.copy() function make a copy of this TimedeltaIndex object. The function also sets the Name and dtype attributes on the new object
Syntax : TimedeltaIndex.copy(name=None, deep=False, dtype=None, **kwargs)
Parameters :
name : string, optional
deep : boolean, default False
dtype : numpy dtype or pandas typeReturn : copy : Index
Example #1: Use TimedeltaIndex.copy() function to make a copy of the given TimedeltaIndex object.
# importing pandas as pd import pandas as pd # Create the first TimedeltaIndex object tidx = pd.TimedeltaIndex(start ='1 days 02:00:12.001124', periods = 5, freq ='N', name ='Koala') # Print the TimedeltaIndex object print(tidx) |
Output :
Now we will use the TimedeltaIndex.copy() function to make a copy of the tidx object and will set the name of the copied object to ‘New_koala’.
# make a copy and set the name tidx_copy = tidx.copy(name ='New_koala') # print the new object print(tidx_copy) |
Output :
As we can see in the output, the TimedeltaIndex.copy() function has made a copy of the object and the function has also set the name.
Example #2: Use TimedeltaIndex.copy() function to check if the passed label is present in the Index or not.
# importing pandas as pd import pandas as pd # Create the TimedeltaIndex object tidx = pd.TimedeltaIndex(data =['06:05:01.000030', '+23:59:59.999999', '22 day 2 min 3us 10ns', None]) # Print the TimedeltaIndex object print(tidx) |
Output :
Now we will use the TimedeltaIndex.copy() function to make a copy of the tidx object and will set the name of the copied object to ‘New_koala’. We will also change the dtype of the object to str.
# make a copy, set the name and change the dtype tidx_copy = tidx.copy(dtype ='str', name ='New_koala') # print the new object print(tidx_copy) |
Output :
As we can see in the output, the TimedeltaIndex.copy() function has made a copy of the object and also notice the dtype of the new object.
