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.argmin() function returns the indices of the minimum values along an axis in the TimedeltaIndex object. The function is similar to numpy.ndarray.argmin.
Syntax : TimedeltaIndex.argmin(axis=None, *args, **kwargs)
Parameters :
axis : NoneReturn : integer index value
Example #1: Use TimedeltaIndex.argmin() function to find the indices of the minimum value in 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 print the index of the minimum value in tidx object.
# return the index of minimum value. tidx.argmin() |
Output :
As we can see in the output, the TimedeltaIndex.argmin() function has 0 indicating that the minimum value in tidx object is present at 0th index.
Example #2: Use TimedeltaIndex.argmin() function to find the indices of the minimum value in the given TimedeltaIndex object.
# importing pandas as pd import pandas as pd # Create the TimedeltaIndex object tidx = pd.TimedeltaIndex(data =['22 days 2 min 3us 10ns', '1 days 06:05:01.000030', '-1 days + 23:59:59.999999']) # Print the TimedeltaIndex object print(tidx) |
Output :
Now we will print the index of the minimum value in tidx object.
# return the index of minimum value. tidx.argmin() |
Output :
As we can see in the output, the TimedeltaIndex.argmin() function has 2 indicating that the minimum value in tidx object is present at 2nd index.
