Skip to main content
Practice

Generating Arrays (arange, linspace, zeros, ones)

NumPy gives you built-in functions to quickly create arrays — without manually typing the values.

These are useful for building test data or initializing arrays.


np.arange(start, stop, step)​

Creates evenly spaced values from start to stop (excluding stop).

np.arange(0, 10, 2)  # [0 2 4 6 8]

np.linspace(start, stop, num)​

Creates a specific number of evenly spaced values including the stop value.

np.linspace(0, 1, 5)  # [0.   0.25 0.5  0.75 1.0]

np.zeros(shape) and np.ones(shape)​

Create arrays filled with all 0s or all 1s. Pass in a shape like (3,) or (2, 3).

np.zeros((2, 2))  # [[0. 0.]
                  #  [0. 0.]]

Summary​

  • arange: spaced by step (like range())
  • linspace: spaced by number of points
  • zeros / ones: fill arrays with fixed values

What’s Next​

You’ll now try generating different types of arrays using these tools in Jupyter.