feature_ scaling

def sort(any):
    less=[]
    equal=[]
    large=[]
    if len(any)>1:
        pivot=any[0]
        for x in any:
            if x<pivot:
                less.append(x)
            if x==pivot:
                equal.append(x)
            if x>pivot:
                large.append(x)
        return sort(less)+equal+sort(large)
    else:
        return any
        
def featureScaling(arr):
    frsh=[]
    new= sort(arr)
    
    maxm= new[-1]
    minm= new[0]

    if len(new)>3:
        
        
        for x in new[1:-2]:
            
            scaled= (x-minm)/(maxm-minm)
            frsh.append(scaled)
        
        return frsh
    else:
        
        answer= float(float(new[1]-minm)/float(maxm-minm))
        return answer
    
        
        
        
        

# tests of your feature scaler--line below is input data
data = [115, 140, 175]


print featureScaling(data)