The following article will discuss the NumPy array and how we can convert it to a standard python list. The NumPy module provides functions that help us achieve this.
A NumPy array consists of a grid of values of a similar type. The indexing in a NumPy array is done using non-negative integer values. The dimension of an array is considered to be its “rank.” An array shape is determined by the number of elements along each dimension of the array.
About The Module
The Python NumPy module provides us with packages for array processing. It allows us to create “array objects” of multiple dimensions. Various functions for manipulating these array objects are also provided within the module. It is the most fundamental library for scientific computation in Python.
About The Function
The function provides us with a list of all the data elements from the NumPy array.
Parameters – NONE
Return – A nested list consisting of the array elements
How To Convert a NumPy Array to a Python List
One Dimensional Array
In this program, we are passing the
tolist function to a one-dimensional NumPy array.
import numpy as np myArray = np.array([3,2,5,9]) print(myArray) print(type(myArray)) #converting to a list arrList = myArray.tolist() print(arrList) # type of arrList print(type(arrList))
[3 2 5 9] <class 'numpy.ndarray'> [3, 2, 5, 9] <class 'list'>
Two Dimensional Array
Similar to the previous example, we will pass a two-dimensional NumPy array in this demonstration.
import numpy as np myArray = np.array([[3,2,5], [4,4,3], [9,5,6]]) print(myArray) print(type(myArray)) #converting to a list arrList = myArray.tolist() print(arrList) # type of arrList print(type(arrList))
[[3 2 5] [4 4 3] [9 5 6]] <class 'numpy.ndarray'> [[3, 2, 5], [4, 4, 3], [9, 5, 6]] <class 'list'>
Passing NumPy Array tolist Function Over a 2nd Axis
Let’s look at how we can split an n-dimensional NumPy array within an internal axis.
Consider an array of shape (3,133,78,78,78,1) within a list of 150 arrays. In order to retrieve a list based on an internal axis, let’s pass the
swapaxes() function allows us to interchange two or more axes of an array in Python.
So we should pass: np.swapaxes(nameofArray,0,1) and place the 150 dimensions in the beginning. Furthermore,
list() can be passed to retrieve the complete list
Appending NumPy Array to a List
The following demonstration shows us how we can append NumPy Arrays to a Python List.
import numpy as np a = np.empty((3), int) listINIT =  for idx in range(4): for i in range(3): a[i] = idx*10 + i print("idx =",idx,"; a =",a) listINIT.append(a.copy()) print("listINIT =",listINIT)
NumPy tolist vs. Python list Function
|NumPy tolist||Python list|
|NumPy tolist provides complete conversion of nested lists (lists of lists).||The list can only iterate over a one-dimension array.|
|tolist only works on objects that implement the said method.||A list will work on any iterable object.|
|The tolist function belongs to an external module NumPy||list function is an inbuilt and predefined function in Python.|
How To Convert a 2D NumPy Array to a List of Lists using tolist?
Let’s look at how we can convert a 2D array into nested lists.
For this procedure, we will primarily be using the Numpy array tolist function.
import numpy as np myArray = np.array([[3, 6, 9, 12], [56, 63, 12, 77], [12, 32, 12, 2]]) print(myArray) listOfList = myArray.tolist() print(listOfList)
[[ 3 6 9 12] [56 63 12 77] [12 32 12 2]] [[3, 6, 9, 12], [56, 63, 12, 77], [12, 32, 12, 2]]
How To Convert N-Dimensional NumPy Array To a List of Tuples?
In this program, we will see how we can convert multiple dimensional arrays into a List of Tuples.
import numpy as np myArray = np.array([[[3,12]], [[56, 77]]]) # Converting to a list of tuples my reshaping myArray list(map(tuple, myArray.reshape((2, 2))))
[(3, 12), (56, 77)]
How To Display Arrays Without The Square Brackets
We can display the elements alone within an array by excluding the square brackets. Let’s how that’s achieved in One and Two Dimensional Arrays.
import numpy as np myArray = np.array([3,5,6]) print(*myArray, sep=', ')
3, 5, 6
Implementing the same program as the 1D array will only remove the outermost brackets. Therefore, let’s look at a different program.
import numpy as np myArray = np.array([[3,5,6], [8,2,3], [9, 82, 0]]) print(str(myArray).replace(' [', '').replace('[', '').replace(']', ''))
3 5 6 8 2 3 9 82 0
Flattening a List of NumPy Arrays
numpy.contactenate function, we can concatenate elements from an input list into a single array object.
import numpy as np contactElem = np.concatenate(input_list).ravel()
The final output can be displayed in a list format like so:
import numpy as np contactElemList = np.concatenate(input_list).ravel().tolist()
Converting Multidimensional Arrays into Lists of Lists
We can use the
.tolist() function to convert NumPy matrices to lists.
Let’s look at the following demonstration:
import numpy as np myArray = np.array([[3,5,6], [8,2,3], [9, 82, 0]]) listArray = myArray.tolist() type(listArray) print(listArray)
[[3, 5, 6], [8, 2, 3], [9, 82, 0]]
The time complexity for
.tolist() is O(n), where n is the number of elements in the list.
NumPy Arrays are faster than Python Lists. This is due to the fact that an array consists of elements of similar types in adjacent memory locations. At the same time, List elements can be of different types located in non-adjacent memory locations.
In this article, we have looked at the versatility of NumPy arrays and how they differ from regular Python lists. We have demonstrated the use cases for NumPy array tolist and various scenarios where the function comes in handy.
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