Series:
0    1
1    2
2    3
3    4
4    5
dtype: int64
Array:
[1 2 3 4 5]

The program first prints the Series series1. After that, it uses the Series.to_numpy() function to convert the Series to a NumPy array. [1 2 3 4 5] is the NumPy array.

How to convert a pandas DataFrame to a NumPy array?

As discussed in one of our previous articles, the pandas DataFrame is a two-dimensional data structure. It is also a labeled data structure. Both the rows and the columns of a DataFrame can be labeled. If we do not provide any labels, then by default the labels start from 0.

In Python, we can use the DataFrame.to_numpy() function to convert a pandas DataFrame to a NumPy array. For example, we can use the following Python code to convert a DataFrame to a NumPy array.

import pandas

df = pandas.DataFrame([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]])
print("DataFrame: \n", df)
array2 = df.to_numpy()
print("Array: \n", array2)

Here, we are first creating a DataFrame df. After that, we are using the DataFrame.to_numpy() function to convert the DataFrame into a NumPy array.

The output of the program will be:

DataFrame: 
    0   1   2   3
0  1   2   3   4
1  5   6   7   8
2  9  10  11  12
Array: 
 [[ 1  2  3  4]
 [ 5  6  7  8]
 [ 9 10 11 12]]