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.

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### 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

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Tutorials on pandas series –

- 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