Add Row to pandas DataFrame in Python (2 Examples)

In this tutorial, I’ll show how to append a new row to a pandas DataFrame in Python programming.

The content of the post looks as follows:

Let’s take a look at some Python codes in action:

Example Data & Libraries

First, we need to load the pandas library:

import pandas as pd                                           # Import pandas library to Python

The data below will be used as basement for this Python programming language tutorial:

data = pd.DataFrame({'x1':range(8, 3, - 1),                  # Create example DataFrame
                     'x2':[2, 7, 5, 1, 3],
                     'x3':range(11, 16)})
print(data)                                                  # Print example DataFrame

Table 1 shows that our example data consists of five rows and the three variables “x1”, “x2”, and “x3”.

Next, we have to create a list that we can insert as a new row to our DataFrame later on:

new_row = [1, 2, 3]                                          # Create new row
print(new_row)                                               # Print new row
# [1, 2, 3]

As you can see, our new row that we will combine with our DataFrame contains the values 1, 2, and 3.

Example 1: Append New Row at Bottom of pandas DataFrame

In this example, I’ll explain how to append a list as a new row to the bottom of a pandas DataFrame.

For this, we can use the loc attribute as shown below:

data_new1 = data.copy()                                      # Create copy of DataFrame
data_new1.loc[5] = new_row                                   # Append new row
print(data_new1)                                             # Print updated DataFrame

As shown in Table 2, the previous Python programming syntax has created a new pandas DataFrame with an additional row in the last line of our data.

Example 2: Insert New Row in the Middle of pandas DataFrame

In this section, I’ll show how to insert a new row within a pandas DataFrame.

Again, we can use the loc attribute for this task. However, this time, we have to specify a value in between the indices of our input DataFrame.

As you can see below, we are using the index position 2.5 to add a new row in the middle of our data.

Furthermore, we use the sort_index and reset_index functions to reset the indices of our new DataFrame (note that this step is optional):

data_new2 = data.copy()                                      # Create copy of DataFrame
data_new2.loc[2.5] = new_row                                 # Insert new row
data_new2 = data_new2.sort_index().reset_index(drop = True)  # Reset index
print(data_new2)                                             # Print updated DataFrame

By running the previous Python programming code, we have created Table 3, i.e. another pandas DataFrame with a new row in the middle of the data.

Video & Further Resources

Do you need further info on the Python programming syntax of this article? Then I recommend having a look at the following video on the YouTube channel of Ryan Noonan. He’s explaining how to concatenate rows to a pandas DataFrame in another example in the video:

Furthermore, you could read the related articles on this website:

• Add Column to pandas DataFrame
• Extract Top & Bottom N Rows from pandas DataFrame
• Drop Rows with Blank Values from pandas DataFrame
• Insert Column at Specific Position of pandas DataFrame
• Manipulate pandas DataFrames in Python
• Introduction to the pandas Library in Python
• Python Programming Overview

Summary: You have learned in this article how to concatenate and stack a new row to a pandas DataFrame to create a union between a DataFrame and a list (i.e. rbind) in the Python programming language. Let me know in the comments section below, in case you have any further questions.