# Convert Python list to numpy array

In this article, you will learn how to convert a Python list to a numpy array. **NumPy** is the fundamental package for scientific computing with Python. It is a highly optimized library for numerical operations. The support of NumPy makes the task easier. Several libraries like OpenCV, SciPy, Matplotlib when combining with NumPy increase the number of weapons in your arsenal. This module contains a number of useful concepts such as the ability to create multidimensional array objects, perform mathematical operations, tools for integrating C/C++ and Fortran code.

A **list** is a sequence of indexed and ordered values like an array. It is mutable, which means we can change the order of elements in a list. A list in Python is a linear data structure that can hold heterogeneous elements. It is flexible to shrink and grow and there is no need to declare it. But, an array can hold homogeneous elements. It requires less memory space than a list. In Python, the arrays are implemented using the **NumPy** library.

During programming, there may be instances when you will need to change the existing lists to an array to play out a specific task on them. These are the processes to convert **Python list to numpy array**.

## Method 1: Using numpy.array()

The array object in Python is called **ndarray**. The **array()** function is used to a NumPy **ndarray** object. In the given example, we have defined a list, which then converted into an array using the **numpy.array()** function and printed the array -

```
# importing numpy library
import numpy
# initilizing list
number_list =[43, 12, 19, 6, 23, 17, 31]
# converting list to array
arr = numpy.array(number_list)
# printing list
print ("List: ", number_list)
# printing array
print ("Array: ", number_list)
```

The above code returns the following output -

```
List: [43, 12, 19, 6, 23, 17, 31]
Array: [43, 12, 19, 6, 23, 17, 31]
```

## Method2: using numpy.asarray()

Both **numpy.array()** and **numpy.asarray()** methods can convert structured data into **ndarray**, but the main difference is that when the data source is ndarray, **array** will create a copy of the object array and would not reflect changes to the original array and occupy new memory space, but **asarray** will not.

```
# importing numpy library
import numpy
# initilizing list
number_list =[11, 42, 24, 12, 9, 42, 92]
# converting list to array
arr = numpy.asarray(number_list)
# printing list
print ("List: ", number_list)
# printing array
print ("Array: ", number_list)
```

The above code returns the following output -

```
List: [11, 42, 24, 12, 9, 42, 92]
Array: [11, 42, 24, 12, 9, 42, 92]
```

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