You can use the following syntax to convert a pandas DataFrame to a NumPy array:

df.to_numpy()

The following examples show how to use this syntax in practice.

**Example 1: Convert DataFrame with Same Data Types**

The following code shows how to convert a pandas DataFrame to a NumPy array when each of the columns in the DataFrame is the same data type:

import pandas as pd #create data frame df1 = pd.DataFrame({'rebounds': [7, 7, 8, 13, 7, 4], 'points': [5, 7, 7, 9, 12, 9], 'assists': [11, 8, 10, 6, 6, 5]}) #view data frame print(df1) rebounds points assists 0 7 5 11 1 7 7 8 2 8 7 10 3 13 9 6 4 7 12 6 5 4 9 5 #convert DataFrame to NumPy array new = df1.to_numpy() #view NumPy array print(new) [[ 7 5 11] [ 7 7 8] [ 8 7 10] [13 9 6] [ 7 12 6] [ 4 9 5]] #confirm thatnewis a NumPy array print(type(new)) <class 'numpy.ndarray'> #view data type print(new.dtype) int64

The Numpy array has a data type of **int64** since each column in the original pandas DataFrame was an integer.

**Example 2: Convert DataFrame with Mixed Data Types**

The following code shows how to convert a pandas DataFrame to a NumPy array when the columns in the DataFrame are not all the same data type:

import pandas as pd #create data frame df2 = pd.DataFrame({'player': ['A', 'B', 'C', 'D', 'E', 'F'], 'points': [5, 7, 7, 9, 12, 9], 'assists': [11, 8, 10, 6, 6, 5]}) #view data frame print(df2) player points assists 0 A 5 11 1 B 7 8 2 C 7 10 3 D 9 6 4 E 12 6 5 F 9 5 #convert DataFrame to NumPy array new = df2.to_numpy() #view NumPy array print(new) [['A' 5 11] ['B' 7 8] ['C' 7 10] ['D' 9 6] ['E' 12 6] ['F' 9 5]] #confirm thatnewis a NumPy array print(type(new)) <class 'numpy.ndarray'> #view data type print(new.dtype) object

The Numpy array has a data type of **object** since not every column in the original pandas DataFrame was the same data type.

**Example 3: Convert DataFrame & Set NA Values**

The following code shows how to convert a pandas DataFrame to a NumPy array and specify the values to be set for any NA values in the original DataFrame:

import pandas as pd #create data frame df3 = pd.DataFrame({'player': ['A', 'B', pd.NA, 'D', 'E', 'F'], 'points': [5, 7, pd.NA, 9, pd.NA, 9], 'assists': [11, 8, 10, 6, 6, 5]}) #view data frame print(df3) player points assists 0 A 5 11 1 B 7 8 2 <NA> <NA> 10 3 D 9 6 4 E <NA> 6 5 F 9 5 #convert DataFrame to NumPy array new = df3.to_numpy(na_value='none') #view NumPy array print(new) [['A' 5 11] ['B' 7 8] ['none' 'none' 10] ['D' 9 6] ['E' 'none' 6] ['F' 9 5]] #confirm thatnewis a NumPy array print(type(new)) <class 'numpy.ndarray'> #view data type print(new.dtype) object

**Additional Resources**

How to Create a Pandas DataFrame from a NumPy Array

How to Convert a List to a DataFrame in Pandas

How to Convert a DataFrame to List in Pandas