How to use Pandas.DataFrame.assign(**kwargs) In Python Pandas
It Assigns new columns to a DataFrame and returns a new object with all existing columns to new ones. Existing columns that are re-assigned will be overwritten.
Syntax: Pandas.DataFrame.assign(**kwargs)
Parameters : **kwargsdict of {str: callable or Series}
Returns : DataFrame
Let’s understand with examples:
First, create a simple DataFrame.
Python3
# importing pandas as pd import pandas as pd # creating the dataframe df = pd.DataFrame({"Name": ['Anurag', 'Manjeet', 'Shubham', 'Saurabh', 'Ujjawal'], "Address": ['Patna', 'Delhi', 'Coimbatore', 'Greater noida', 'Patna'], "ID": [20123, 20124, 20145, 20146, 20147], "Sell": [140000, 300000, 600000, 200000, 600000]}) print("Original DataFrame :") display(df) |
Output:
Add a new column:
Python3
new_df = df.assign(profit=[40000, 20000, 30000, 60000, 200000]) new_df |
Output:
Add a new column with Default Value:
Python3
new_df = df.assign(profit='NAN') new_df |
Output:
Add Column to Pandas DataFrame with a Default Value
The three ways to add a column to Pandas DataFrame with Default Value.
- Using pandas.DataFrame.assign(**kwargs)
- Using [] operator
- Using pandas.DataFrame.insert()