Python | Pandas Index.argsort()
Last Updated :
29 Nov, 2019
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 Index.argsort()
function returns the integer indices that would sort the index. By default the sorting order has been set to increasing order.
Syntax: Index.argsort(*args, **kwargs)
Parameters :
*args : Passed to numpy.ndarray.argsort
**kwargs : Passed to numpy.ndarray.argsort
Returns : numpy.ndarray
Integer indices that would sort the index if used as an indexer
Example #1: Use Index.argsort()
function to find the order of indices which would sort the given Index.
import pandas as pd
df = pd.Index([ 17 , 69 , 33 , 5 , 10 , 74 , 10 , 5 ])
df
|
Output :
Let’s find the ordering of the indices which would sort the Index.
Output :
As we can see in the output, the function has returned the ordering of the indices which would sort the given Index. We can verify that by printing the Index based on the ordering.
Output :
As we can see in the output, it is printed in a sorted order.
Example #2: Use Index.argsort()
function to find the order of indices which would sort the given Index.
import pandas as pd
df = pd.Index([ 'Sam' , 'Alex' , 'Olivia' ,
'Dan' , 'Brook' , 'Katherine' ])
df
|
Output :
Let’s find the ordering of the indices which would sort the Index.
Output :
As we can see in the output, the function has returned the ordering of the indices which would sort the given Index. We can verify that by printing the Index based on the ordering.
Output :
As we can see in the output, it is printed in a sorted order.
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