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.sort_values() function is used to sort the index values. The function return a sorted copy of the index. Apart from sorting the numerical values, the function can also sort string type values.
Syntax: Index.sort_values(return_indexer=False, ascending=True)
Parameters :
return_indexer : Should the indices that would sort the index be returned.
ascending : Should the index values be sorted in an ascending order.Returns : Sorted copy of the index.
sorted_index : pandas.Indexindexer : numpy.ndarray, optional
The indices that the index itself was sorted by.
Example #1: Use Index.sort_values() function to sort the values present in the index.
# importing pandas as pd import pandas as pd # Creating the index idx = pd.Index(['Beagle', 'Pug', 'Labrador', 'Sephard', 'Mastiff', 'Husky']) # Print the index idx |
Output :
Now we will sort the index labels in the ascending order.
# Sorting the index labels idx.sort_values(ascending = True) |
Output :
As we can see in the output, the function has returned an index with its labels sorted.
Example #2: Use Index.sort_values() function to sort the index labels in the descending order.
# importing pandas as pd import pandas as pd # Creating the index idx = pd.Index([22, 14, 8, 56, 27, 21, 51, 23]) # Print the index idx |
Output :
Now we will sort the index labels in non-increasing order.
# sort the values in descending order idx.sort_values(ascending = False) |
Output :
As we can see in the output, the function has returned a new index with its labels sorted in decreasing order.
