Convert Pandas Series to a NumPy Array

In this tutorial, we will look at how to convert a pandas series to a NumPy array.

How to convert a pandas series to an array?

There are a number of ways to get an array from a pandas series. You can directly get a numpy array of series values by accessing the .values attribute of the series or you can use the pandas series to_numpy() function. The following is the syntax to use the above methods:

# using .values
arr = s.values
# using to_numpy()
arr = s.to_numpy()

Here, s is the pandas series you want to convert. Both the methods return a numpy array of the series values.

Examples

Let’s look at some examples of using the above methods to create a numpy array from a series. First, we’ll create a sample pandas series which we will be using throughout this tutorial.

import pandas as pd

# pandas series Wimbledon winners from 2015 to 2019
wimbledon_winners = pd.Series(index=[2015, 2016, 2017, 2018, 2019],
                   data=['Novak Djokovic', 'Andy Murray', 'Roger Federer', 'Novak Djokovic', 'Novak Djokovic'],
                   name='Name')

# display the series
print(wimbledon_winners)

Output:

2015    Novak Djokovic
2016       Andy Murray
2017     Roger Federer
2018    Novak Djokovic
2019    Novak Djokovic
Name: Name, dtype: object

You can see the contents of the series object above. Let’s confirm the type of the object.

# check the type
print(type(wimbledon_winners))

Output:

<class 'pandas.core.series.Series'>

We now have a pandas series containing the name of Wimbledon Winners from 2015 to 2019 with the year as its index.

1. Series to numpy array using .values

You can easily get a numpy array of series values by accessing the .values attribute of the series. Let’s do that with our “wimbledon_winners” series created above.

arr = wimbledon_winners.values
# check the type
print(type(arr))
# print the content
print(arr)

Output:

<class 'numpy.ndarray'>
['Novak Djokovic' 'Andy Murray' 'Roger Federer' 'Novak Djokovic'
 'Novak Djokovic']

You can see that .values gives a numpy.ndarray object of the series values.

2. Series to numpy array using to_numpy()

Alternatively, you can use the pandas series to_numpy() function to create a numpy array of series values. Let’s apply this function to the “wimbledon_winners” series.

arr = wimbledon_winners.to_numpy()
# check the type
print(type(arr))
# print the content
print(arr)

Output:

<class 'numpy.ndarray'>
['Novak Djokovic' 'Andy Murray' 'Roger Federer' 'Novak Djokovic'
 'Novak Djokovic']

You can see that the resulting numpy array has all the values from the series “wimbledon_winners”.

For more on the to_numpy() function, refer to its documentation.

With this, we come to the end of this tutorial. The code examples and results presented in this tutorial have been implemented in a Jupyter Notebook with a python (version 3.8.3) kernel having pandas version 1.0.5

• Convert Pandas Series to a DataFrame
• Convert Pandas Series to a List
• Convert Pandas Series to a NumPy Array
• Convert Pandas Series to a Dictionary
• Sort a Pandas Series
• Append Two Pandas Series
• Apply a Function to a Pandas Series
• Pandas – Shift column values up or down
• Plot a Histogram of Pandas Series Values
• Create a Pie Chart of Pandas Series Values
• Plot a Bar Chart of Pandas Series Values
• Create a Boxplot from Pandas Series Values
• Create a Density Plot from Pandas Series Values