Creating Arrays

The most direct way to create an array is np.array.

The input is often a list. The result is a NumPy array.

Vectors

A one-dimensional array is often used as a vector:

The shape is (3,), which means one axis with three values.

Matrices

A two-dimensional array is often used as a matrix:

The shape is (2, 3): two rows, three columns.

For a regular two-dimensional numerical array, every row must have the same length. If one row has fewer values, there is no single rectangular shape.

Create vectors and matrices

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Useful constructors

NumPy can create common arrays:

np.arange(5) produces values from 0 up to 4, like range(5) but as an array.

grid = np.zeros((2, 3))

The tuple (2, 3) is a shape.

Choose clear starting data

When learning, prefer tiny arrays whose values you can inspect by eye. If you cannot explain a shape with a small example, a larger example will not help.

Exercise: Create a vector

Which expression creates a NumPy array from the values 1, 2, and 3?

Answer it first, then check.

Hint

Pass one Python list containing the three values to np.array.

Solution

Use:

np.array([1, 2, 3])

The list supplies the values; np.array constructs the NumPy array.