Python:NumPy .tolist()

The .tolist() function in NumPy converts an array into a nested Python list and returns it. Each element in the array is converted into the closest compatible built-in Python type using the .item() function. The attribute a.ndim represents the number of dimensions (axes) of the array. When a.ndim is 0, the result of the operation is a simple scalar, as the depth of the nested list is 0.

Syntax

ndarray.tolist()

• ndarray: The array to be converted.

Example

The following example creates an ndarray named arr and converts it into a nested Python list arr_list using .tolist():

import numpy as np

# Creating an array
arr = np.uint32([1, 2])

# Converting the array into a Python list using list()
arr_list = list(arr)

# Checking the output
print(arr_list)

# Checking the output type
print(type(arr_list[0]))

# Converting the array into a Python list using .tolist()
arr_tolist = arr.tolist()

# Checking the output
print(arr_tolist)

# Checking the output type
print(type(arr_tolist[0]))

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This produces the following output:

[1, 2]
<class 'numpy.uint32'>
[1, 2]
<class 'int'>

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As observed, although the resulting lists are similar, i.e., [1, 2], the types of their elements differ when using list() versus .tolist().

Codebyte Example

Here is a codebyte example to understand the working of the .tolist() function for converting a 2D array into a Python list:

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