CODEWITHSUNDEEP
numpynumpy-ndarray
bib
bib

Reputation: 1040

How to Normalize the values between zero and one?

I have a ndarray of shape (74,):

[-1.995   1.678  -2.535   1.739  -1.728  -1.268  -0.727  -3.385  -2.348
     -3.021   0.5293 -0.4573  0.5137 -3.047  -4.75   -1.847   2.922  -0.989
     -1.507  -0.9224 -2.545   6.957   0.9985 -2.035  -3.234  -2.848  -1.971
     -3.246   2.057  -1.991  -6.27    9.22    0.4045 -2.703  -1.577   4.066
      7.215  -4.07   12.98   -3.02    1.456   9.44    6.49    0.272   2.07
      1.625  -3.531  -2.846  -4.914  -0.536  -3.496  -1.095  -2.719  -0.5825
      5.535  -0.1753  3.658   4.234   4.543  -0.8384 -2.705  -2.012  -6.56
     10.5    -2.021  -2.48    1.725   5.69    3.672  -6.855  -3.887   1.761
      6.926  -4.848 ]

I need to normlize this vector where the values become between [0,1] and then the sum of the values inside this vector = 1.

Upvotes: 2

Views: 1063

Answers (1)

Dwa
Dwa

Reputation: 673

You can try this formula to make it between [0, 1]:

min_val = np.min(original_arr)
max_val = np.max(original_arr)
normalized_arr = (original_arr - min_val) / (max_val - min_val)

You can try this formula to make the sum of the array to be 1:

new_arr = original_arr / original_arr.sum()

Upvotes: 5

Related Questions