"Unlock the Power of NumPy: Transform Your Arrays into Lists the Easy Way"
Are you wondering how to transform a NumPy array into a Python list while preserving the , ,
, and tags? Follow these simple guidelines to do it efficiently. For this conversion, you will need to use the ndarray.tolist() function. Fortunately, this method is uncomplicated and doesn't call for any parameters. When used, it will present a Python list from an array. During the conversion process, the items get transformed into the closest compatible built-in Python type.
If you are working with a one-dimensional array, it will return a list with the array objects. On the other hand, if you're handling a multidimensional array, it will give you a list of lists with the objects. In this article, we will explain how to go about utilizing the tolist() method to convert a numpy array into a list. We will also provide examples to help you better understand the concept.
Please note that in Python NumPy, an ndarray is a homogeneous multidimensional array of fixed-size items of the same type. To create an ndarray object in NumPy, you can use NumPy.array().
If you're in a rush, we have provided a few quick examples below to assist you in converting a NumPy array to a list in Python.
# Quick Examples
# Convert One-dimensional NumPy Array to List
# Example 1: Use tolist() Method
Begin by utilizing the tolist() method to convert a one-dimensional NumPy array into a list. First, you must create an ndarray using the array() function, followed by utilizing the tolist() function to convert it into a list. The array() function receives a Python list as an argument.
import numpy as np
arr = np.array([3, 6, 9])
list = arr.tolist()
print(f'List: {list}')
# Example 2: Convert Multi-dimensional NumPy Array to List
If you have a two-dimensional NumPy array, you can utilize the same tolist() function to convert it to a list. Begin by passing two Python lists as arguments to the np.array() function to create a two-dimensional array.
import numpy as np
arr = np.array([[3,6,9], [2,5,8]])
list = arr.tolist()
print(f'List: {list}')
Alternatively, you can accomplish this in a single statement.
import numpy as np
arr=np.array([[3,5,9], [2,7,8],[3,6,2]]).tolist()
print(arr)
Using the above methods should provide you with the desired output that will help you achieve your objective of converting NumPy arrays to Python lists.
An alternative method of converting NumPy ndarray to a list involves using the python list() function. However, it's important to note that this won't change the elements into python type, which means the values in the list will still be in numpy types.
To demonstrate using an example, consider the following code:
- ```python
- import numpy as np
- a = np.array([1, 2])
- a_list = list(a)
- print(a_list)
- pront(type(a_list))
- print(type(a_list[0]))
- ```
- This will output:
- ```
- [1, 2]
- ```
If you encounter an error when trying to convert a 0-D array (zero-dimensional) to a list, you can resolve it using the ndarray.tolist() function. Here's an example:
```python
import numpy as np
a = np.array(1)
a_list = list(a)
```
This will result in the following error:
- ```
- TypeError: iteration over a 0-d array
- ```
- To convert the 0D array, you can use the ndarray.tolist() function like so:
- ```python
- arr = np.array(1)
- print(arr.tolist())
- print(type(arr.tolist()))
- ```
- This will output:
- ```
- 1
- ```
In summary, this article has provided examples of how to convert NumPy array to list using tolist() and list() methods. If the array is one-dimensional, a list with the array elements is returned as a list of objects. For a multi-dimensional array, a nested list is returned as a list of list of objects.
For more information, please visit: https://numpy.org/doc/stable/reference/generated/numpy.ndarray.tolist.html

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