Add multiple columns to a data frame using Dictionary and zip()

Add multiple columns to a data frame using Dataframe.insert() method

Using Dict and zip() we can create a mapping of key values, which can be assigned to a new column name.

Python3

# importing pandas library
import pandas as pd
 
# creating and initializing a nested list
students = [['jackma', 34, 'Sydeny', 'Australia'],
            ['Ritika', 30, 'Delhi', 'India'],
            ['Vansh', 31, 'Delhi', 'India'],
            ['Nany', 32, 'Tokyo', 'Japan'],
            ['May', 16, 'New York', 'US'],
            ['Michael', 17, 'las vegas', 'US']]
 
# Create a DataFrame object
df = pd.DataFrame(students,
                  columns=['Name', 'Age', 'City', 'Country'],
                  index=['a', 'b', 'c', 'd', 'e', 'f'])
 
# creating 2 lists 'ids' and 'marks'
ids = [11, 12, 13, 14, 15, 16]
marks=[85,41,77,57,20,95,96]
 
# Creating columns 'ID' and 'Uni_marks'  
# using Dictionary and zip() 
df['ID'] = dict(zip(ids, df['Name']))
df['Uni_Marks'] = dict(zip(marks, df['Name']))
   
# Displaying the Data frame
df

Output :

Added multiple columns using Dictionary and zip()

Add multiple columns to dataframe in Pandas

In Pandas, we have the freedom to add columns in the data frame whenever needed. There are multiple ways to add columns to pandas dataframe.

Add multiple columns to a data frame using Dictionary and zip()

Python3

Add multiple columns to dataframe in Pandas

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