How to use pandas.DataFrame.insert() In Python Pandas
Add new column into DataFrame at specified location.
Syntax: DataFrame.insert(loc, column, value, allow_duplicates=False)
Parameters
loc : int Insertion index. Must verify 0 <= loc <= len(columns).
column : str, number, or hashable object Label of the inserted column.
value : int, Series, or array-like
allow_duplicates : bool, optional
Let’s understand with examples:
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 with default value:
Python3
df.insert( 2 , "expenditure" , 4500 , allow_duplicates = False ) 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()