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How to sort a dataFrame in python pandas by two or more columns?

Given a Pandas DataFrame, we have to sort a dataFrame by two or more columns.
Submitted by Pranit Sharma, on July 28, 2022

Pandas is a special tool that allows us to perform complex manipulations of data effectively and efficiently. Inside pandas, we mostly deal with a dataset in the form of DataFrame. DataFrames are 2-dimensional data structures in pandas. DataFrames consist of rows, columns, and data.

Sorting refers to rearranging a series or a sequence in a particular fashion (ascending, descending, or in any specific pattern). Sorting in pandas DataFrame is required for effective analysis of the data. Pandas allow us to sort the DataFrame using pandas.DataFrame.sort_values() method.

Syntax:

DataFrame.sort_values(
    by, 
    axis=0, 
    ascending=True, 
    inplace=False, 
    kind='quicksort', 
    na_position='last', 
    ignore_index=False, 
    key=None
    )

Parameters:

• by: name of sequence or column by which it should sort.
• axis: Column to be sorted.(0 or 'axis' 1 or 'column') by default its 0 (column number)
• There are some other parameters like: Ascending, inplace, kind, etc.

Let us understand with the help of an example,

Python code to sort a dataFrame in pandas by two or more columns

# Import pandas package
import pandas as pd

# import numpy package
import numpy as np

# Creating a dictionary
d = {
    'Name': ['Rajeev', 'Akhilesh', 'Sonu', 'Timak', 'Divyansh', 'Megha'],
    'Age': [56, 23, 28, 92, 77, 32]
}

# Creating a Dataframe
df = pd.DataFrame(d)

# Dispaly the dataframe
print('Created DataFrame:\n',df,"\n")

# Using the sorting function
result = df.sort_values(by=['Age'], ascending=True)

# Display result
print('Result:\n',result)

Output:

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