Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index.
Pandas Series.sort_index()
function is used to sort the index labels of the given series object.
Syntax: Series.sort_index(axis=0, level=None, ascending=True, inplace=False, kind=’quicksort’, na_position=’last’, sort_remaining=True)
Parameter :
axis : Axis to direct sorting. This can only be 0 for Series.
level : If not None, sort on values in specified index level(s).
ascending : Sort ascending vs. descending.
inplace : If True, perform operation in-place.
kind : Choice of sorting algorithm.
na_position : Argument ‘first’ puts NaNs at the beginning, ‘last’ puts NaNs at the end.
sort_remaining : If true and sorting by level and index is multilevel, sort by other levels too (in order) after sorting by specified level.Returns : Series
Example #1: Use Series.sort_index()
function to sort the index labels of the given series object.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([ 'New York' , 'Chicago' , 'Toronto' , 'Lisbon' , 'Rio' , 'Moscow' ]) # Create the Index index_ = [ 'City 5' , 'City 6' , 'City 4' , 'City 2' , 'City 3' , 'City 1' ] # set the index sr.index = index_ # Print the series print (sr) |
Output :
Now we will use Series.sort_index()
function to sort the index labels of the given series object.
# sort the index labels sr.sort_index() |
Output :
As we can see in the output, the Series.sort_index()
function has successfully sorted the index labels of the given series object.
Example #2: Use Series.sort_index()
function to sort the index labels of the given series object.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([ 19.5 , 16.8 , 22.78 , 20.124 , 18.1002 ]) # Create the Index index_ = [ 5 , 3 , 2 , 1 , 4 ] # set the index sr.index = index_ # Print the series print (sr) |
Output :
Now we will use Series.sort_index()
function to sort the index labels of the given series object.
# sort the index labels sr.sort_index() |
Output :
As we can see in the output, the Series.sort_index()
function has successfully sorted the index labels of the given series object.