In this very short tutorial today we’ll learn how you can turn a Pandas Series to a Numpy Array in Python.

## Step 1: Create a Pandas Series

We’ll use a simple Series made of air temperature observations:

```
# We'll first import Pandas and Numpy
import pandas as pd
import numpy as np
# Creating the Pandas Series
min_temp = pd.Series ([42.9, 38.9, 38.4, 42.9, 42.2])
```

## Step 2: Series conversion to NumPy array

We’ll go over two different methods:

### Using np.array()

We are able to use the np.array method for the conversion:

`np.array(min_temp, dtype=float)`

*Note: The Dtype parameter is optional and should be specified if you are interested to modify the default data type for the array, which will be determined by NumPy.*

### Using Pandas method to_numpy()

Starting with Pandas 0.24, the newly method to_numpy is available.

Note: your Pandas version can be determined by running the following command:

```
import pandas as pd
pd.__version__
```

Using **to_numpy** is simple, and requires only the Pandas library and is overall faster.

`min_temp.to_numpy()`

Which will obviously return the following array:

array([42.9, 38.9, 38.4, 42.9, 42.2])

## Convert Series to string arrays

You can use the object dtype to get an array of strings.

`my_u_array = np.array(min_temp, dtype= object)`

array([42.9, 38.9, 38.4, 42.9, 42.2], dtype=object)