# How to Convert List to NumPy Array (With Examples)

You can use the following basic syntax to convert a list in Python to a NumPy array:

```import numpy as np

my_list = [1, 2, 3, 4, 5]

my_array = np.asarray(my_list)
```

The following examples shows how to use this syntax in practice.

### Example 1: Convert List to NumPy Array

The following code shows how to convert a list in Python to a NumPy array:

```import numpy as np

#create list of values
my_list = [3, 4, 4, 5, 7, 8, 12, 14, 14, 16, 19]

#convert list to NumPy array
my_array = np.asarray(my_list)

#view NumPy array
print(my_array)

[ 3  4  4  5  7  8 12 14 14 16 19]

#view object type
type(my_array)

numpy.ndarray```

Note that you can also use the dtype argument to specify a certain data type for the new NumPy array when performing the conversion:

```import numpy as np

#create list of values
my_list = [3, 4, 4, 5, 7, 8, 12, 14, 14, 16, 19]

#convert list to NumPy array
my_array = np.asarray(my_list, dtype=np.float64)

#view data type of NumPy array
print(my_array.dtype)

float64
```

### Example 2: Convert List of Lists to NumPy Array of Arrays

The following code shows how to convert a list of lists to a NumPy array of arrays:

```import numpy as np

#create list of lists
my_list_of_lists = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]

#convert list to NumPy array
my_array = np.asarray(my_list_of_lists)

#view NumPy array
print(my_array)

[[1 2 3]
[4 5 6]
[7 8 9]]
```

We can then use the shape function to quickly get the dimensions of the new array of arrays:

```print(my_array.shape)

(3, 3)
```

This tells us that the NumPy array of arrays has three rows and three columns.