How to Add Data to Specific Row and Column in Dataframe in Python

To add data to a specific row and column of a dataframe, you can use the loc[] function.

The following example shows how to add data to a specific row and column of a dataframe using the loc[] function.

Using loc[] Function

We can use the loc[] function to add data to a specific row and column in a dataframe.

Suppose we have the following dataframe:

# Import pandas library
import pandas as pd

# Create dataframe
Office_Stuff = pd.DataFrame({
    'Date': ['01-03-2023', '01-03-2023', '01-03-2023', '01-03-2023', '02-03-2023', '02-03-2023'],
    'Product_Code': ['A-101', 'A-102', 'A-103', 'B-101', 'B-102', 'B-104'],
    'Product_Name': ['Laptop', 'Mobile', 'Printer', 'Keyboard', 'Scanner', 'Mouse'],
    'Price': [4500, 550, 250, 50, 350, 50],
    'Status': [1, 1, 1, 0, 1, 1]
})

# Adding data to a specific row and column
Office_Stuff.loc[Office_Stuff['Product_Code'] == 'B-101', 'Price'] = 500

# Print updated dataframe
print(Office_Stuff)

Output: 👇️

         Date Product_Code Product_Name  Price  Status
0  01-03-2023        A-101       Laptop   4500       1
1  01-03-2023        A-102       Mobile    550       1
2  01-03-2023        A-103      Printer    250       1
3  01-03-2023        B-101     Keyboard    500       0
4  02-03-2023        B-102      Scanner    350       1
5  02-03-2023        B-104        Mouse     50       1

In this example, we use the loc[] function to add data to the Price column for the row where the Product_Code is ‘B-101’.