How to Append Row From Another Dataframe to Dataframe in Python

To append a row from another dataframe to a dataframe in Python, you can use the concat() function from the pandas library.

Method: Use concat() Function

pd.concat([df1, df2], ignore_index=True)

The following example shows how to append a row from another dataframe to a dataframe in Python using the concat() function.

Using concat() Function

We can use the concat() function to append rows from one dataframe to another.

Suppose we have the following dataframes:

# 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]
})

# Create a new dataframe
New_Office_Stuff = pd.DataFrame({
    'Date': ['03-03-2023', '03-03-2023'],
    'Product_Code': ['A-104', 'B-105'],
    'Product_Name': ['Chair', 'Table'],
    'Price': [100, 200],
    'Status': [1, 0]
})

# Append the new rows to the original dataframe
Office_Stuff = pd.concat([Office_Stuff, New_Office_Stuff], ignore_index=True)

# Print the 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     50       0
4  02-03-2023        B-102      Scanner    350       1
5  02-03-2023        B-104        Mouse     50       1
6  03-03-2023        A-104        Chair    100       1
7  03-03-2023        B-105        Table    200       0

In this example, we use the concat() function to append rows from the New_Office_Stuff dataframe to the Office_Stuff dataframe.