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()