Occasionally you may want to add a NumPy array as a new column to a pandas DataFrame.

Fortunately you can easily do this using the following syntax:

df['new_column'] = array_name.tolist()

This tutorial shows a couple examples of how to use this syntax in practice.

**Example 1: Add NumPy Array as New Column in DataFrame**

The following code shows how to create a pandas DataFrame to hold some stats for basketball players and append a NumPy array as a new column titled ‘blocks’:

import numpy as np import pandas as pd #create pandas DataFrame df = pd.DataFrame({'points': [25, 12, 15, 14, 19, 23, 25, 29], 'assists': [5, 7, 7, 9, 12, 9, 9, 4], 'rebounds': [11, 8, 10, 6, 6, 5, 9, 12]}) #create NumPy array for 'blocks' blocks = np.array([2, 3, 1, 0, 2, 7, 8, 2]) #add 'blocks' array as new column in DataFrame df['blocks'] = blocks.tolist() #display the DataFrame print(df) points assists rebounds blocks 0 25 5 11 2 1 12 7 8 3 2 15 7 10 1 3 14 9 6 0 4 19 12 6 2 5 23 9 5 7 6 25 9 9 8 7 29 4 12 2

Note that the new DataFrame now has an extra column titled *blocks*.

**Example 2: Add NumPy Matrix as New Columns in DataFrame**

The following code shows how to create a pandas DataFrame to hold some stats for basketball players and append a NumPy array as a new column titled ‘blocks’:

import numpy as np import pandas as pd #create pandas DataFrame df = pd.DataFrame({'points': [25, 12, 15, 14, 19, 23 #create NumPy matrix mat = np.matrix([[2, 3], [1, 0], [2, 7], [8, 2], [3, 4], [7, 7], [7, 5], [6, 3]]) #add NumPy matrix as new columns in DataFrame df_new = pd.concat([df, pd.DataFrame(mat)], axis=1) #display new DataFrame print(df_new) points assists rebounds 0 1 0 25 5 11 2 3 1 12 7 8 1 0 2 15 7 10 2 7 3 14 9 6 8 2 4 19 12 6 3 4 5 23 9 5 7 7 6 25 9 9 7 5 7 29 4 12 6 3

Note that the names of the columns for the matrix that we added to the DataFrame are given default column names of **0** and **1**.

We can easily rename these columns using the **df.columns** function:

#rename columns df_new.columns = ['pts', 'ast', 'rebs', 'new1', 'new2'] #display DataFrame print(df_new) pts ast rebs new1 new2 0 25 5 11 2 3 1 12 7 8 1 0 2 15 7 10 2 7 3 14 9 6 8 2 4 19 12 6 3 4 5 23 9 5 7 7 6 25 9 9 7 5 7 29 4 12 6 3

**Additional Resources**

How to Stack Multiple Pandas DataFrames

How to Merge Two Pandas DataFrames on Index

How to Convert Pandas DataFrame to NumPy Array

How to Rename Columns in Pandas