Pandas: Sort rows or columns in Dataframe based on values using Dataframe.sort_values()

How to sort rows or columns in Dataframe based on values using Dataframe.sort_values() in Python ?

In this article we will get to know about how to sort rows in ascending & descending order based on values in columns and also sorting columns based on value in rows using member function DataFrame.sort_values().

DataFrame.sort_values() :

Pandas library contains a Dataframe class which provide a function to arrange the contents of dataframe.

Syntax : DataFrame.sort_values(by, axis=0, ascending=True, inplace=False, kind='quicksort', na_position='last')

where,

• by:  Column names or index labels where sorting is to be done.
• axis:  If axis=0. names by argument will be taken as column names and If axis=1, names by argument will be taken as row index labels
• ascending:  If True: Ascending Sorting , Else: Descending Sorting
• inplace: When true in-place operation performed in dataframe
• na_position: If True: It will sort the current dataframe , Else: Return a sorted copy of dataframe instead of modifying the dataframe.

Sorting Dataframe rows based on a single column :

To sort rows in dataframe based on ‘Team’ column, we will pass ‘Team’ as argument.

#Program :

import pandas as sc

# List of Tuples as Players
players = [ ('Curran', 325, 'CSK') ,
             ('Ishan', 481, 'MI' ) ,
             ('Vijay', 106, 'SRH') ,
             ('Pant', 224, 'Delhi' ) ,
             ('Seifert', 65, 'KKR' ) ,
             ('Hooda', 440, 'PK' )
              ]

# To Create DataFrame object
datafObjs = sc.DataFrame(players, columns=['Name', 'Runs', 'Team'], index=['i', 'ii', 'iii', 'iv', 'v', 'vi'])

# Sorting the rows of dataframe by column 'Team'
datafObjs = datafObjs.sort_values(by ='Team' )

print("Now the sorted Dataframe based on column 'Team' is : ")
print(datafObjs)

Output :
 Now the sorted Dataframe based on column 'Team' is :
        Name  Runs   Team
i     Curran   325    CSK
iv      Pant   224  Delhi
v    Seifert    65    KKR
ii     Ishan   481     MI
vi     Hooda   440     PK
iii    Vijay   106    SRH

• Pandas : Sort a DataFrame based on column names or row index labels using Dataframe.sort_index()
• Pandas : Convert Dataframe column into an index using set_index() in Python
• Pandas Dataframe: Get minimum values in rows or columns & their index position

Sorting Dataframe rows based on multiple column :

To sort all rows of dataframe based on Team & Runs column.

#Program :

import pandas as sc

# List of Tuples as Players
players = [ ('Curran', 325, 'CSK') ,
             ('Ishan', 481, 'MI' ) ,
             ('Vijay', 106, 'SRH') ,
             ('Pant', 224, 'Delhi' ) ,
             ('Seifert', 65, 'KKR' ) ,
             ('Hooda', 440, 'PK' )
              ]

# To Create DataFrame object
datafObjs = sc.DataFrame(players, columns=['Name', 'Runs', 'Team'], index=['i', 'ii', 'iii', 'iv', 'v', 'vi'])

# Sorting the rows of dataframe by column 'Team'
datafObjs = datafObjs.sort_values(by =['Runs', 'Team'])

print("Now the sorted Dataframe on the basis of columns 'Name' & 'Marks' : ")
print(datafObjs)

Output :
Now the sorted Dataframe on the basis of columns 'Name' & 'Marks' :
        Name   Runs   Team
v     Seifert    65       KKR
iii    Vijay      106     SRH
iv     Pant      224    Delhi
i      Curran   325     CSK
vi     Hooda   440     PK
ii     Ishan      481     MI

Sorting Dataframe rows based on columns in Descending Order :

Here we will sort the dataframe in descending order by passing value as false in argument ascending.

#Program :

import pandas as sc

# List of Tuples as Players
players = [ ('Curran', 325, 'CSK') ,
             ('Ishan', 481, 'MI' ) ,
             ('Vijay', 106, 'SRH') ,
             ('Pant', 224, 'Delhi' ) ,
             ('Seifert', 65, 'KKR' ) ,
             ('Hooda', 440, 'PK' )
              ]

# To Create DataFrame object
datafObjs = sc.DataFrame(players, columns=['Name', 'Runs', 'Team'], index=['i', 'ii', 'iii', 'iv', 'v', 'vi'])

# Sortimg rows of dataframe by column 'Name' in descending manner
datafObjs = datafObjs.sort_values(by ='Name' , ascending=False)

print("Now the sorted Dataframe on basis of column 'Name' in Descending manner : ")
print(datafObjs)

Output :
Now the sorted Dataframe on basis of column 'Name' in Descending manner :
        Name   Runs   Team
iii     Vijay      106    SRH
v     Seifert     65      KKR
iv    Pant       224     Delhi
ii     Ishan      481     MI
vi     Hooda   440     PK
i      Curran     325    CSK

Sorting Dataframe rows based on a column in Place :

Here we will sort the dataframe based on single column in place with argument inplace and value True.

#Program :

import pandas as sc

# List of Tuples as Players
players = [ ('Curran', 325, 'CSK') ,
             ('Ishan', 481, 'MI' ) ,
             ('Vijay', 106, 'SRH') ,
             ('Pant', 224, 'Delhi' ) ,
             ('Seifert', 65, 'KKR' ) ,
             ('Hooda', 440, 'PK' )
              ]

# To Create DataFrame object
datafObjs = sc.DataFrame(players, columns=['Name', 'Runs', 'Team'], index=['i', 'ii', 'iii', 'iv', 'v', 'vi'])

# Sorting e rows of the dataframe by column 'Name' inplace
datafObjs.sort_values(by='Team' , inplace=True)

print("Now the sorted Dataframe based on a single column 'Team' inplace : ")
print(datafObjs)

Output :
Now the sorted Dataframe based on a single column 'Team' inplace :
        Name  Runs   Team
i      Curran   325    CSK
iv     Pant     224     Delhi
v      Seifert    65    KKR
ii      Ishan    481     MI
vi     Hooda   440     PK
iii     Vijay     106     SRH

Sorting columns of a Dataframe based on a single or multiple rows :

Let’s take a example where column of a dataframe is to be sorted on the  basis of single or multiple rows.

#program :

import pandas as sc

# List of Tuples as matrix
matrix = [(11, 2, 33),
          (4, 55, 6),
          (77, 8, 99),
          ]

# To create a DataFrame object like a Matrix
datafObjs = sc.DataFrame(matrix, index=list('abc'))

print("Sorting the daataframe based on single rows or multiple rows: ")
print(datafObjs)

Output :
Sorting the daataframe based on single rows or multiple rows:
    0   1   2
a  11   2  33
b   4  55   6
c  77   8  99

Sorting columns of a Dataframe based on a single row :

Now from above dataframe let’s sort the dataframe on basis of ‘b’ row.

#program :

import pandas as sc

# List of Tuples as matrix
matrix = [(11, 2, 33),
          (4, 55, 6),
          (77, 8, 99),
          ]

# To create a DataFrame object like a Matrix
datafObjs = sc.DataFrame(matrix, index=list('abc'))
datafObjs = datafObjs.sort_values(by ='b', axis=1)

print("Now the sorted Dataframe on the basis of single row index label 'b' : ")
print(datafObjs)

Output :
Now the sorted dataframe is sorted on the basis of row index label 'b' :
    0   2   1
a  11  33   2
b   4   6  55
c  77  99   8

Sorting columns of a Dataframe in Descending Order based on a single row :

Here we will sort columns of the dataframe in descending order based on single row.

Here we will sort columns of a Dataframe on basis of multiple rows by passing value in ascending as false.

#Program :

import pandas as sc

# List of Tuples as matrix
matrix = [(11, 2, 33),
          (4, 55, 6),
          (77, 8, 99),
          ]

# To create a DataFrame object like a Matrix
datafObjs = sc.DataFrame(matrix, index=list('abc'))

# Sorting the columns of a dataframe in descending order based on a single row with index label 'b'
datafObjs = datafObjs.sort_values(by='b', axis=1, ascending=False)

print("Now the sorted Dataframe on the basis of single row index label 'b' in descending order :")
print(datafObjs)

Output :
Now the sorted Dataframe on the basis of single row index label 'b' in descending order :

    1   2   0
a   2  33  11
b  55   6   4
c   8  99  77

Sorting columns of a Dataframe based on a multiple rows :

 Here the columns of dataframe are sorted on the  basis of multiple rows with passing labels ‘b’ & ‘c’ and axis=1.

#program :

import pandas as sc

# List of Tuples as matrix
matrix = [(11, 2, 33),
          (4, 55, 6),
          (77, 8, 99),
          ]

# To create a DataFrame object like a Matrix
datafObjs = sc.DataFrame(matrix, index=list('abc'))

# Sorting columns of the dataframe based on a multiple row with index labels 'b' & 'c'
datafObjs = datafObjs.sort_values(by =['b' , 'c' ], axis=1)

print("Now the sorted Dataframe based on multiple rows index label 'b' & 'c' :")
print(datafObjs)

Output :
Now the sorted Dataframe based on multiple rows index label 'b' & 'c' :

    0   2   1
a  11  33   2
b   4   6  55
c  77  99   8

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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