# Normalization of volume

suppose we have volumes every minute like below

100, 200 , 19,  0 , 200 , 12 , 100


I want to convert all these numbers to less than 10 , where 10 is max and 1 is min.

I can do this with normalisation but problem occurs when there is some sudden high volume comes like below

100, 200 , 19,  0 , 200 , 12 , 20000


where when I use normalization for past past 100 volumes, , this 20000 is affecting all other volumes.

Is there something I can do by taking averages of volumes and do normalisation for that or something ?

>>> arr = np.array([100,200,19,0,200,12,20000])