In this article, our basic task is to sort the data frame based on two or more columns. For this, Dataframe.sort_values() method is used. This method sorts the data frame in Ascending or Descending order according to the columns passed inside the function.
First, Let’s Create a Dataframe:
Python3
#import python library import pandas as pd # dictionary data_frame = { 'name' : [ 'Akash Kumar' , 'Diksha Tewari' , 'Bhawna Gourh' , 'Ayush Sharma' ], 'age' : [ 20 , 21 , 22 , 23 ], 'favorite_color' : [ 'black' , 'Yellow' , 'Pink' , "Orange" ], 'grade' : [ 88 , 92 , 95 , 70 ] } # create data frame with indexing df = pd.DataFrame(data_frame, index = [ 1 , 2 , 3 , 4 ]) # printing the dataframe df |
Output:
Example 1: Sort Dataframe based on ‘age'(in descending order) and ‘grade’ (in ascending order) column.
Python3
# sort the dataframe # based on age and grade df.sort_values([ 'age' , 'grade' ], ascending = [ False , True ]) |
Output:
Example 2: Sort Dataframe based on ‘name’ and ‘favorite_color’ column in ascending order.
Python3
# sort the dataframe based # on name and favorite_colr df.sort_values([ 'name' , 'favorite_color' ], ascending = [ True , True ]) |
Output:
Example 3: In-place sorting of Dataframe based on ‘grade’ and ‘favorite_color’ column. In case of in-place sorting, Dataframe.sort_values() method returns nothing it performs changes in the actual dataframe.
Python3
df.sort_values([ "grade" , "favorite_color" ], axis = 0 , ascending = True , inplace = True , na_position = 'first' ) # printing the dataframe df |
Output:
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