Merge two Pandas DataFrames on certain columns

Sort the Pandas DataFrame by two or more columns

Last Updated : 17 Aug, 2020

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:

Dataframe

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:

sorted dataframe based on age and grade

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:

sorted dataframe based on name and color

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:

sorted dataframe based on grade and favorite color

Merge two Pandas DataFrames on certain columns

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