Pandas : Sort a DataFrame based on column names or row index labels using Dataframe.sort_index()

Sorting a DataFrame based on column names or row index labels using Dataframe.sort_index() in Python

In this article we will discuss how we organize the content of data entered based on column names or line reference labels using Dataframe.sort_index ().

Dataframe.sort_index():

In the Python Pandas Library, the Dataframe section provides a member sort sort_index () to edit DataFrame based on label names next to the axis i.e.

DataFrame.sort_index(axis=0, level=None, ascending=True, inplace=False, kind='quicksort', na_position='last', sort_remaining=True, by=None)

Where,

• axis :If the axis is 0, then the data name will be sorted based on the line index labels. The default is 0
• ascending :If the axis is 1, then the data name will be sorted based on column names.
• inplace : If the type of truth in the rise of another type arrange in order. The default is true
• na_position :  If True, enable localization in Dataframe. Determines NaN status after filter i.e. irst puts NaNs first, finally puts NaNs at the end.

It returns the edited data object. Also, if the location dispute is untrue then it will return a duplicate copy of the provided data, instead of replacing the original Dataframe. While, if the internal dispute is true it will cause the current file name to be edited.

Let’s understand some examples,

# Program :

import pandas as pd
# List of Tuples
students = [ ('Rama', 31, 'canada') ,
             ('Symon', 23, 'Chennai' ) ,
             ('Arati', 16, 'Maharastra') ,
             ('Bhabani', 32, 'Kolkata' ) ,
             ('Modi', 33, 'Uttarpradesh' ) ,
             ('Heeron', 39, 'Hyderabad' )
              ]
# Create a DataFrame object
dfObj = pd.DataFrame(students, columns=['Name', 'Marks', 'City'], index=['b', 'a', 'f', 'e', 'd', 'c'])
print(dfObj)

Output :
    Name   Marks  City
b  Rama     31   canada
a  Symon   23   Chennai
f   Arati      16   Maharastra
e  Bhabani  32  Kolkata
d  Modi      33  Uttarpradesh
c  Heeron  39   Hyderabad

Now let’s see how we organize this DataFrame based on labels i.e. columns or line reference labels,

Sort rows of a Dataframe based on Row index labels :

Sorting by line index labels we can call sort_index() in the data name item.

import pandas as pd
# The List of Tuples
students = [ ('Rama', 31, 'canada') ,
             ('Symon', 23, 'Chennai' ) ,
             ('Arati', 16, 'Maharastra') ,
             ('Bhabani', 32, 'Kolkata' ) ,
             ('Modi', 33, 'Uttarpradesh' ) ,
             ('Heeron', 39, 'Hyderabad' )
              ]
# To create DataFrame object 
dfObj = pd.DataFrame(students, columns=['Name', 'Marks', 'City'], index=['b', 'a', 'f', 'e', 'd', 'c'])
# By sorting the rows of dataframe based on row index label names
modDFObj = dfObj.sort_index()
print(' Dataframes are in sorted oreder of index value given:')
print(modDFObj)

Output :
Dataframes are in sorted oreder of index value given:
    Name    Marks        City
a Symon      23         Chennai
b Rama        31         canada
c Heeron     39         Hyderabad
d Modi        33         Uttarpradesh
e Bhabani    32         Kolkata
f Arati          16         Maharastra

As we can see in the output lines it is sorted based on the reference labels now. Instead of changing the original name data backed up an edited copy of the dataframe.

Sort rows of a Dataframe in Descending Order based on Row index labels :

Sorting based on line index labels in descending order we need to pass the argument = False in sort_index() function in the data object object.

import pandas as pd
# The List of Tuples
students = [ ('Rama', 31, 'canada') ,
             ('Symon', 23, 'Chennai' ) ,
             ('Arati', 16, 'Maharastra') ,
             ('Bhabani', 32, 'Kolkata' ) ,
             ('Modi', 33, 'Uttarpradesh' ) ,
             ('Heeron', 39, 'Hyderabad' )
              ]
# To create DataFrame object 
dfObj = pd.DataFrame(students, columns=['Name', 'Marks', 'City'], index=['b', 'a', 'f', 'e', 'd', 'c'])
# By sorting the rows of dataframe in descending order based on row index label names
conObj = dfObj.sort_index(ascending=False)
print('The Contents of Dataframe are sorted in descending Order based on Row Index Labels are of :')
print(conObj)

The Contents of Dataframe are sorted in descending Order based on Row Index Labels are of :
     Name       Marks          City
f      Arati          16          Maharastra
e     Bhabani     32          Kolkata
d     Modi        33           Uttarpradesh
c     Heeron     39           Hyderabad
b     Rama       31           canada
a     Symon     23           Chennai

As we can see in the output lines it is sorted by destructive sequence based on the current reference labels. Also, instead of changing the original data name it restored the edited copy of the data.

Sort rows of a Dataframe based on Row index labels in Place :

Filtering a local data name instead of finding the default copy transfer inplace = True in sort_index () function in the data object object to filter the data name with local reference label labels i.e.

import pandas as pd
# The List of Tuples
students = [ ('Rama', 31, 'canada') ,
             ('Symon', 23, 'Chennai' ) ,
             ('Arati', 16, 'Maharastra') ,
             ('Bhabani', 32, 'Kolkata' ) ,
             ('Modi', 33, 'Uttarpradesh' ) ,
             ('Heeron', 39, 'Hyderabad' )
              ]
# To create DataFrame object 
dfObj = pd.DataFrame(students, columns=['Name', 'Marks', 'City'], index=['b', 'a', 'f', 'e', 'd', 'c'])
#By sorting the rows of dataframe in Place based on row index label names
dfObj.sort_index(inplace=True)
print('The Contents of Dataframe are sorted in Place based on Row Index Labels are of :')
print(dfObj)

Output :
The Contents of Dataframe are sorted in Place based on Row Index Labels are of :
     Name     Marks      City
a    Symon     23       Chennai
b     Rama     31        canada
c   Heeron     39     Hyderabad
d     Modi     33     Uttarpradesh
e  Bhabani     32       Kolkata
f    Arati       16       Maharastra

Sort Columns of a Dataframe based on Column Names :

To edit DataFrame based on column names we can say sort_index () in a DataFrame object with an axis= 1 i.e.

import pandas as pd
# The List of Tuples
students = [ ('Rama', 31, 'canada') ,
             ('Symon', 23, 'Chennai' ) ,
             ('Arati', 16, 'Maharastra') ,
             ('Bhabani', 32, 'Kolkata' ) ,
             ('Modi', 33, 'Uttarpradesh' ) ,
             ('Heeron', 39, 'Hyderabad' )
              ]
# To create DataFrame object 
dfObj = pd.DataFrame(students, columns=['Name', 'Marks', 'City'], index=['b', 'a', 'f', 'e', 'd', 'c'])
# By sorting a dataframe based on column names
conObj = dfObj.sort_index(axis=1)
print('The Contents are of Dataframe sorted based on Column Names are in the type :')
print(conObj)

Output :
The Contents are of Dataframe sorted based on Column Names are in the type :
           City          Marks     Name
b        canada         31      Rama
a       Chennai         23     Symon
f      Maharastra     16     Arati
e       Kolkata          32     Bhabani
d  Uttarpradesh     33     Modi
c     Hyderabad     39      Heeron

As we can see, instead of changing the original data name it returns a fixed copy of the data data based on the column names.

Sort Columns of a Dataframe in Descending Order based on Column Names :

By sorting DataFrame based on column names in descending order, we can call sort_index () in the DataFrame item with axis = 1 and ascending = False i.e.

import pandas as pd
# The List of Tuples
students = [ ('Rama', 31, 'canada') ,
             ('Symon', 23, 'Chennai' ) ,
             ('Arati', 16, 'Maharastra') ,
             ('Bhabani', 32, 'Kolkata' ) ,
             ('Modi', 33, 'Uttarpradesh' ) ,
             ('Heeron', 39, 'Hyderabad' )
              ]
# To create DataFrame object 
dfObj = pd.DataFrame(students, columns=['Name', 'Marks', 'City'], index=['b', 'a', 'f', 'e', 'd', 'c'])
# By sorting a dataframe in descending order based on column names
conObj = dfObj.sort_index(ascending=False, axis=1)
print('The Contents of Dataframe sorted in Descending Order based on Column Names are of :')
print(conObj)

Output :
The Contents of Dataframe sorted in Descending Order based on Column Names are of :
Name  Marks          City
b     Rama     31        canada
a    Symon     23       Chennai
f    Arati     16    Maharastra
e  Bhabani     32       Kolkata
d     Modi     33  Uttarpradesh
c   Heeron     39     Hyderabad

Instead of changing the original data name restore the edited copy of the data based on the column names (sorted by order)

Sort Columns of a Dataframe in Place based on Column Names :

Editing a local data name instead of obtaining an approved copy pass input = True and axis = 1 in sort_index () function in the dataframe object to filter the local data name by column names i.e.

import pandas as pd
# The List of Tuples
students = [ ('Rama', 31, 'canada') ,
             ('Symon', 23, 'Chennai' ) ,
             ('Arati', 16, 'Maharastra') ,
             ('Bhabani', 32, 'Kolkata' ) ,
             ('Modi', 33, 'Uttarpradesh' ) ,
             ('Heeron', 39, 'Hyderabad' )
              ]
# To create DataFrame object 
dfObj = pd.DataFrame(students, columns=['Name', 'Marks', 'City'], index=['b', 'a', 'f', 'e', 'd', 'c'])
# By sorting a dataframe in place based on column names
dfObj.sort_index(inplace=True, axis=1)
print('The Contents of Dataframe sorted in Place based on Column Names are of:')
print(dfObj)

Output :
The Contents of Dataframe sorted in Place based on Column Names are of:
City  Marks     Name
b        canada     31     Rama
a       Chennai     23    Symon
f    Maharastra     16    Arati
e       Kolkata     32  Bhabani
d  Uttarpradesh     33     Modi
c     Hyderabad     39   Heeron

Want to expert in the python programming language? Exploring Python Data Analysis using Pandas tutorial changes your knowledge from basic to advance level in python concepts.

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