We’ll discuss the following five ways:

**Method 1**: Actually Creating an Array of Strings**Method 2**: Converting Strings to Float Array**Method 3**: Converting Strings to Int Array**Method 4**: How to Convert a Multi-Dimensional List of Strings to a Multi-Dimensional NumPy Array?**Method 5**: How to Convert a List of Strings to a NumPy Array with a Specific Shape?

Let’s get started! π©βπ»π

## Method 1: Actually Creating an Array of Strings

In the unlikely case that you actually want to convert a list of strings to a NumPy array of strings, you can pass it in the `np.array()`

function.

Here’s a minimal example:

import numpy as np list_of_strings = ['string1', 'string2', 'string3'] numpy_array = np.array(list_of_strings) print(numpy_array) # ['string1' 'string2' 'string3']

In this code, `list_of_strings`

is your list of strings, and `numpy_array`

is the resulting numpy array.

## Method 2: Converting Strings to Float Array

You can convert a list of strings to a numpy array of floats using the `numpy.array()`

function along with the `astype()`

method.

Here’s a concise example:

import numpy as np list_of_strings = ['1.1', '2.2', '3.3'] numpy_array = np.array(list_of_strings, dtype=float) print(numpy_array) # [1.1 2.2 3.3]

In this code, `list_of_strings`

is your list of strings, and `numpy_array`

is the resulting numpy array of floats. The `dtype=float`

argument in `np.array()`

ensures the conversion to float.

## Method 3: Converting Strings to Int Array

You can convert a list of strings to a numpy array of integers using the `numpy.array()`

function along with the `dtype`

parameter.

Here’s a similar example:

import numpy as np list_of_strings = ['1', '2', '3'] numpy_array = np.array(list_of_strings, dtype=int) print(numpy_array) # [1 2 3]

In this code, `list_of_strings`

is your list of strings, and `numpy_array`

is the resulting numpy array of integers. The `dtype=int`

argument in `np.array()`

ensures the conversion to integer.

## Method 4: How to Convert a Multi-Dimensional List of Strings to a Multi-Dimensional NumPy Array?

You can convert a multi-dimensional list of strings to a multi-dimensional numpy array using the `numpy.array()`

function.

Here’s an example:

import numpy as np lst = [['1', '2'], ['3', '4'], ['5', '6']] numpy_array = np.array(lst, dtype=int) print(numpy_array) ''' [[1 2] [3 4] [5 6]] '''

The variable `lst`

is your multi-dimensional list of strings, and `numpy_array`

is the resulting multi-dimensional numpy array of integers. The `dtype=int`

argument in `np.array()`

ensures the conversion to integer. You can change the `dtype`

to `float`

or any other type as per your requirement.

## Method 5: How to Convert a List of Strings to a NumPy Array with a Specific Shape?

You can convert a list of strings to a numpy array with a specific shape using the `numpy.array()`

function and then reshape it using the `reshape()`

method.

Example:

import numpy as np list_of_strings = ['1', '2', '3', '4', '5', '6'] numpy_array = np.array(list_of_strings, dtype=int) # Reshape to desired shape, for example, (3, 2) reshaped_array = numpy_array.reshape((3, 2)) print(reshaped_array) ''' [[1 2] [3 4] [5 6]] '''

In this code, `list_of_strings`

is your list of strings, `numpy_array`

is the resulting numpy array of integers, and `reshaped_array`

is the numpy array reshaped to the desired shape. The `dtype=int`

argument in `np.array()`

ensures the conversion to integer. You can change the `dtype`

to `float`

or any other type as per your requirement.

Please note that the total number of elements in the list should be equal to the product of the dimensions specified in the `reshape()`

method. In this case, the list has 6 elements, and the reshape dimensions are 3 and 2, which multiply to 6. If they don’t match, you’ll get an error.

I have created an in-depth guide on the `reshape()`

method that you should check out to improve your NumPy skills:

While working as a researcher in distributed systems, Dr. Christian Mayer found his love for teaching computer science students.

To help students reach higher levels of Python success, he founded the programming education website Finxter.com that has taught exponential skills to millions of coders worldwide. He’s the author of the best-selling programming books Python One-Liners (NoStarch 2020), The Art of Clean Code (NoStarch 2022), and The Book of Dash (NoStarch 2022). Chris also coauthored the Coffee Break Python series of self-published books. He’s a computer science enthusiast, freelancer, and owner of one of the top 10 largest Python blogs worldwide.

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