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

seriesName.to_numpy()

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

Example 1: Convert Series to NumPy Array

The following code shows how to convert a pandas Series to a NumPy array:

import pandas as pd
import numpy as np

#define series
x = pd.Series([1, 2, 5, 6, 9, 12, 15])

#convert series to NumPy array
new_array = x.to_numpy() 

#view NumPy array
new_array

array([ 1,  2,  5,  6,  9, 12, 15])

#confirm data type
type(new_array)

numpy.ndarray

Using the type() function, we confirm that the pandas Series has indeed been converted to a NumPy array.

Example 2: Convert DataFrame Column to NumPy Array

The following code shows how to convert a column in a pandas DataFrame to a NumPy array:

import pandas as pd
import numpy as np

#define 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]})

#convert 'points' column to NumPy array
new_array = df['points'].to_numpy() 

#view NumPy array
new_array

array([25, 12, 15, 14, 19, 23, 25, 29])

#confirm data type
type(new_array)

numpy.ndarray

We can use dtype() to check the data type of the new NumPy array as well:

#check data type
new_array.dtype

dtype('int64')

We can see that the new NumPy array is an integer.