numpy normalize all values in 2d array code example

Example 1: how to normalize a 1d numpy array

# Foe 1d array
an_array = np.array([0.1,0.2,0.3,0.4,0.5])

norm = np.linalg.norm(an_array)
normal_array = an_array/norm
print(normal_array)

#[0.2,0.4,0.6,0.8,1] (Should be, I didin't run the code)

Example 2: normalize 2d numpy array

import numpy as np

def scale(X, x_min, x_max):
    nom = (X-X.min(axis=0))*(x_max-x_min)
    denom = X.max(axis=0) - X.min(axis=0)
    denom[denom==0] = 1
    return x_min + nom/denom 

X = np.array([
    [ 0,  1],
    [ 2,  3],
    [ 4,  5],
    [ 6,  7],
    [ 8,  9],
    [10, 11],
    [12, 13],
    [14, 15]
])
X_scaled = scale(X, -1, 1)
print(X_scaled)