How to scale and print an array based on its minimum and maximum value?

April 27, 2022

I’m trying to scale the following NumPy array based on its minimum and maximum values.

array = [[17405.051 17442.4   17199.6   17245.65 ]
 [17094.949 17291.75  17091.15  17222.75 ]
 [17289.    17294.9   17076.551 17153.   ]
 [17181.85  17235.1   17003.9   17222.   ]]

Formula used is:
m=(x-xmin)/(xmax-xmin)

wherein m is an individually scaled item, x is an individual item, xmax is the highest value and xmin is the smallest value of the array.

My question is how do I print the scaled array?

P.S. – I can’t use MinMaxScaler as I need to scale a given number (outside the array) by plugging it in the mentioned formula with xmin & xmax of the given array.

I tried scaling the individual items by iterating over the array but I’m unable to put together the scaled array.

I’m new to NumPy, any suggestions would be welcome.
Thank you.

>Solution :

Use method ndarray.min(), ndarray.max() or ndarray.ptp()(gets the range of the values in the array):

>>> ar =  np.array([[17405.051, 17442.4,   17199.6,   17245.65 ],
...  [17094.949, 17291.75,  17091.15,  17222.75 ],
...  [17289.,    17294.9,   17076.551, 17153.   ],
...  [17181.85,  17235.1,   17003.9,   17222.   ]])
>>> min_val = ar.min()
>>> range_val = ar.ptp()
>>> (ar - min_val) / range_val
array([[0.91482554, 1.        , 0.44629418, 0.55131129],
       [0.2076374 , 0.65644242, 0.19897377, 0.4990878 ],
       [0.65017104, 0.663626  , 0.16568073, 0.34002281],
       [0.40581528, 0.527252  , 0.        , 0.49737742]])

I think you should learn more about the basic operation of numpy.