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.argsort() function returns the indices that would sort the index and its underlying data. By default the ordering is of non-decreasing order.
Syntax : TimedeltaIndex.argsort(*args, **kwargs)
Parameters : None
Return : array of indexes
Example #1: Use TimedeltaIndex.argsort() function to find the ordering of elements of the given TimedeltaIndex object that would sort the underlying data in the object.
# importing pandas as pd import pandas as pd # Create the first TimedeltaIndex object tidx = pd.TimedeltaIndex(data =['22 day 2 min 3us 10ns', '06:05:01.000030', '+23:59:59.999999']) # Print the TimedeltaIndex object print(tidx) |
Output :
Now we will find the ordering of the elements which will actually sort the underlying data in the tidx object.
# return the ordering of indices # which will sort the data tidx.argsort() |
Output :
As we can see in the output, the TimedeltaIndex.argsort() function has returned an array containing the indices value which will sort the underlying data of tidx object.
Example #2: Use TimedeltaIndex.argsort() function to find the ordering of elements of the given TimedeltaIndex object that would sort the underlying data in the object.
# importing pandas as pd import pandas as pd # Create the TimedeltaIndex object tidx = pd.TimedeltaIndex(data =['-3 days 02:10:00', '1 days 06:05:01.000030', '1 days 02:00:00'], name ='MyObjejct') # Print the TimedeltaIndex object print(tidx) |
Output :
Now we will find the ordering of the elements which will actually sort the underlying data in the tidx object.
# return the ordering of indices # which will sort the data tidx.argsort() |
Output :
As we can see in the output, the TimedeltaIndex.argsort() function has returned an array containing the indices value which will sort the underlying data of tidx object.
