Generating Numerical Sequences

Numpy comes with in-built functions that allow us to easily generate numerical sequences.

Import Libraries

import numpy as np

arange

By default, arange generates an ndarray that begins at 0 and ends at n - 1, with increments/steps of 1.

print(np.arange(5))

[0 1 2 3 4]

If we state a lower and upper limit, arange generates an ndarray that includes the lower limit, up to but not including the upper limit.

print(np.arange(0, 7))

[0 1 2 3 4 5 6]

We can also control the increment/step between each member of the sequence.

print(np.arange(0, 7, 2))

[0 2 4 6]

It is also possible to create a reverse-ordered sequence.

print(np.arange(4, -1, -1))

[4 3 2 1 0]

linspace

If we know the start, end, the number of samples and require an equally spaced list, the linspace function will be more appropriate.

print(np.linspace(start=0, stop=20, num=5))

[ 0.  5. 10. 15. 20.]

zeros and ones

zeros and ones allow us to easily create single or multi-dimensional arrays that contains all 0s or 1s.

print(np.zeros(5))

[0. 0. 0. 0. 0.]

print(np.zeros([2, 3])) # 2 rows, 3 columns

[[0. 0. 0.]
 [0. 0. 0.]]

print(np.ones(5))

[1. 1. 1. 1. 1.]

print(np.ones([3, 4])) # 3 rows, 4 columns

[[1. 1. 1. 1.]
 [1. 1. 1. 1.]
 [1. 1. 1. 1.]]