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Practice

Generating Arrays (arange, linspace, zeros, ones)

NumPy offers built-in functions that let you create arrays quickly without typing values manually.

These functions are especially useful for generating test data or initializing arrays for computations.


np.arange(start, stop, step)​

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

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

np.linspace(start, stop, num)​

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

np.linspace(start, stop, num)
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 zeros or ones. Pass a shape like (3,) or (2, 3).

np.zeros(shape)
np.zeros((2, 2))  
# [[0. 0.]
#  [0. 0.]]
np.ones(shape)
np.ones((2, 3))  
# [[1. 1. 1.]
#  [1. 1. 1.]]

Summary​

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

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