There is more than one way to create NumPy arrays. The following are some of the ways:

Transforming an existing data structure into an array

Creating an array from scratch and populating it with default or calculated values

Uploading some data from a disk into an array

If you are going to transform an existing data structure, the odds are in favor of you working with a structured list or a pandas DataFrame.

One of the most common situations you will encounter when working with data is the transforming of a list into an array.

When operating such a transformation, it is important to consider the objects the lists contain because this will determine the dimensionality and the dtype of the resulting array.

Let's start with the first example of a list containing just integers:

In: import numpy as npIn: # Transform a list into a uni-dimensional arraylist_of_ints = [1,2,3]Array_1 = np.array(list_of_ints)In: Array_1Out: array([1, 2, 3])

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