5 Best Ways to Convert Python NumPy Array to Normal Array

by

💡 Problem Formulation: Python developers often use NumPy arrays for high-performance numeric computation. However, there are scenarios where a standard Python list is required for certain functionalities not supported by NumPy. This article demonstrates how to convert a NumPy array to a native Python list. Imagine you have a NumPy array np.array([1, 2, 3]) and you want to convert it to [1, 2, 3].

Method 1: Using tolist()

NumPy array objects have a method called tolist(), which returns the array as a nested Python list. Nested lists are created corresponding to the original array’s dimensionality. This method is straightforward and recommended for converting NumPy arrays to native Python lists.

♥️ Info: Are you AI curious but you still have to create real impactful projects? Join our official AI builder club on Skool (only $5): SHIP! - One Project Per Month

Here’s an example:

import numpy as np
numpy_array = np.array([[1, 2, 3], [4, 5, 6]])
normal_list = numpy_array.tolist()
print(normal_list)

Output:

[[1, 2, 3], [4, 5, 6]]

This code snippet converts a 2D NumPy array into a nested Python list using the tolist() method, maintaining the same nested structure.

Method 2: List Comprehension

List comprehension is a concise syntax in Python for creating lists. It can be used to iterate over a NumPy array and create a list by extracting each item. This method offers more control over the conversion process, allowing for element-wise operations if needed.

Here’s an example:

import numpy as np
numpy_array = np.array([[1, 2, 3], [4, 5, 6]])
normal_list = [elem for elem in numpy_array]
print(normal_list)

Output:

[array([1, 2, 3]), array([4, 5, 6])]

In the example above, we created a Python list of NumPy arrays using list comprehension. To get a list of lists, modify the comprehension to [elem.tolist() for elem in numpy_array].

Method 3: Iterating with for loop

Another way to convert a NumPy array to a Python list is by using a simple for loop to iterate through the array and append each element to a new list. This traditional approach is easy to understand and implement, especially for those new to Python.

Here’s an example:

import numpy as np
numpy_array = np.array([1, 2, 3])
normal_list = []
for item in numpy_array:
    normal_list.append(item)
print(normal_list)

Output:

[1, 2, 3]

This snippet shows how to manually iterate over a NumPy array and append each element to a new list, resulting in a normal Python list.

Method 4: Using np.ndarray.flat

The np.ndarray.flat attribute returns an iterator over a NumPy array that can be used to construct a Python list. This method is useful for flattening a multi-dimensional array and then converting it into a list.

Here’s an example:

import numpy as np
numpy_array = np.array([[1, 2, 3], [4, 5, 6]])
normal_list = list(numpy_array.flat)
print(normal_list)

Output:

[1, 2, 3, 4, 5, 6]

Using np.ndarray.flat, we can iterate through a 2D NumPy array in a flat manner and convert it directly to a Python list.

Bonus One-Liner Method 5: Using np.ndarray.flatten() with a List Constructor

A combination of the NumPy flatten() method, which flattens a multi-dimensional array into a one-dimensional array, along with the Python list constructor, can swiftly create a normal list in one line.

Here’s an example:

import numpy as np
numpy_array = np.array([[1, 2, 3], [4, 5, 6]])
normal_list = list(numpy_array.flatten())
print(normal_list)

Output:

[1, 2, 3, 4, 5, 6]

This example demonstrates using flatten() to convert a 2D NumPy array into a flat, one-dimensional array, followed by list constructor to convert it to a Python list.

Summary/Discussion

  • Method 1: tolist(). Simple and direct. Preserves multi-dimensional structure. Inefficient for very large arrays.
  • Method 2: List Comprehension. Customizable and Pythonic. Less straightforward for multi-dimensional arrays.
  • Method 3: for loop. Beginner-friendly. Verbose and potentially slow for large arrays.
  • Method 4: np.ndarray.flat. Good for flattening arrays. Requires additional steps for multi-dimensional arrays.
  • Method 5: flatten() with List Constructor. Clean one-liner. Not suitable if the original multi-dimensional structure is what you need.