How to convert a Python list to a Numpy array? The NumPy library is widely used in Python for scientific computing and working with arrays. NumPy provides a powerful array object called `ndarray`, which allows efficient storage and manipulation of homogeneous data.

You can convert a Python list to a NumPy array using many ways, for example, by using the `numpy.array()`, and `numpy.asarray()` methods. In this article, I will explain how to convert a Python list to Numpy array by using all these methods with examples.

## 1. Quick Examples of Converting Python List to NumPy Arrays

If you are in a hurry, below are some quick examples of how to convert lists to NumPy arrays.

``````
# Quick examples of converting list to numpy arrays

import numpy as np

# Initialize the list
mylist = [2, 4, 6, 8, 10]

# Example 1: Convert python list to Numpy array
# Using numpy.array() method
arr = np.array(mylist)

# Example 2: Convert python list to numpy array
# Using numpy.asarray() method
arr = np.asarray(mylist)

# Example 3: Using numpy.asarray() method
arr = np.asarray(mylist)

# Made another array out of arr
# using asarray function
arr1 = np.asarray(arr)

# Change made in arr1
arr1[3] = 15
``````

## 2. Using numpy.array() Method

You can use the `np.array()` method to convert a list to a NumPy array. For example, you can import the Numpy module and create a list called `mylist`. Then, you can use the `np.array()` method to convert the list into a NumPy array and assign it to the variable arr. Finally, you can print the resulting NumPy array.

NumPy arrays are a powerful data structure for numerical computations in Python, providing efficient and convenient operations on large datasets.

`Note`: The NumPy array representation is slightly different from the list representation. NumPy arrays are printed without commas between the elements.

``````
import numpy as np

# Initialize list
mylist = [2, 4, 6, 8, 10]
print("Original list: ", mylist)

# Convert python list to numpy array
# Using numpy.array() method
arr = np.array(mylist)
print("After converting list to numpy array:", arr)
``````

Yields below output.

## 3. Using numpy.asarray() Method

The `numpy.asarray()` is one of the methods of the NumPy library that converts a given input to an array. If the input is already an array, it returns the same array, but if the input is a list, tuple, or any other sequence-like object, it creates a new array with the same data.

### 3.1 Syntax of numpy.asarray() Method

Following is the syntax of the numpy.asarray() method.

``````
# Syntax of numpy.asarray() method
numpy.asarray(a, dtype=None, order=None)
``````

### 3.2 Parameter of list numpy.asarray()

• `a` – It is the input data. It can be any sequence-like object.
• `dtype` – It is an optional parameter that specifies the data type of the output array. If not provided, NumPy will determine the data type automatically.
• `order` – It is an optional parameter that specifies the memory layout of the output array. It can be “C” for C-style row-major layout, or “F” for Fortran-style column-major layout.

Let’s create a Python list called `mylist` containing five integers. After that, we can convert it into a NumPy array using a `asarray()` method.

``````
import numpy as np

# Initialize list
mylist = [2, 4, 6, 8, 10]
print("Original list: ", mylist)

# Convert python list to numpy array
# Using numpy.asarray() method
arr = np.asarray(mylist)
print("After converting list to numpy array:", arr)
``````

Yields the same output as above.

The key difference between `numpy.array()` and `numpy.asarray()` lies in how they handle the memory of the original object.

• `numpy.array()` – This method always creates a new NumPy array object and copies the data from the original object into the new array. Any modifications made to the new array will not affect the original object, regardless of whether it is a list or another array. Similarly, changes made to the original object will not be reflected in the new array.
• `numpy.asarray()` – When `numpy.asarray()` is used, it checks the type of the original object. If the object is already a NumPy array, it returns a new array object that refers to the same data. Any modifications made to the copied array will also be reflected in the original array, and vice versa.
``````
import numpy as np

# Initialize list
mylist = [2, 4, 6, 8, 10]
print("Original list: ", mylist)

# Convert python list to numpy array
# Using numpy.asarray() method
arr = np.asarray(mylist)
print("List to numpy array:", arr)

# Made another array out of arr
# Using asarray function
arr1 = np.asarray(arr)
print("arr1: " , arr1)

# Change made in arr1
arr1[3] = 15

print("mylist: " , mylist)
print("arr: " , arr)
print("arr1: " , arr1

# Output:
# Original list:  [2, 4, 6, 8, 10]
# List to numpy array: [ 2  4  6  8 10]
# arr1:  [ 2  4  6  8 10]
# mylist:  [2, 4, 6, 8, 10]
# arr:  [ 2  4  6 15 10]
# arr1:  [ 2  4  6 15 10]
``````

## 4. Conclusion

In this article, I have explained how to convert a Python list to NumPy array by using `numpy.array()`, and `numpy.asarray()` methods with examples. Also explained the difference between np.array() and np.asarray() methods.

Happy Learning !!