#note: need a comps.csv file in dir

import pandas as pd
data = pd.read_csv('Comps.csv')

# inp = list(map(str, input().split()))
inp = ["<=30","High","No","Fair"]
l = [x for x in data.keys()]

total = len(data.values)
cl = list(set(data[f'{l[-1]}']))
totlst = [data[data[f'{l[-1]}'] == f"{cl[i]}"].count()[0] for i in range(len(cl))]
problst = [totlst[i]/total for i in range(len(cl))]
dat = []
prob = [1]*len(cl)

for i in range(len(l)-1):
    for j in range(len(cl)):
        dat.append(data[data[f'{l[i]}'] == f"{inp[i]}"][data[f'{l[-1]}'] == f"{cl[j]}"].count()[0])

    for k in range(len(cl)):
        prob[k] *= dat[k]/totlst[k]
    dat.clear()

prob = [prob[i]*problst[i] for i in range(len(cl))]

print("Prediction:",cl[prob.index(max(prob))])