import pandas as pd

data = pd.read_csv('enjoysport.csv')
concepts = data.iloc[:, :-1].values
target = data.iloc[:, -1].values
n=len(concepts[0])-1
specific_h = ['0'] * n 
general_h = ['?'] * n
print("The initialization of the specific and general hypothesis ")
print(" S0:",specific_h,"\n G0:",general_h)

def learn(concepts, target):
    specific_h = concepts[0].copy()
    general_h = [["?" for _ in range(len(specific_h))] for _ in range(len(specific_h))]

    for i, h in enumerate(concepts):
        if target[i] == "yes":
            print(f"\n the {i+1} training instance is Positive \n",concepts[i])
            for x in range(len(specific_h)):
                if h[x] != specific_h[x]:
                    specific_h[x] = '?'
                    general_h[x][x] = '?'
        else:
            print(f"\nThe {i+1} training instance is Negative \n",concepts[i])
            for x in range(len(specific_h)):
                if h[x] != specific_h[x]:
                    general_h[x][x] = specific_h[x]
                else:
                    general_h[x][x] = '?'

        print(f"S{i+1}:\n", specific_h)
        print(f"G{i+1}:\n", general_h)

    general_h = [h for h in general_h if h != ['?' for _ in range(len(specific_h))]]
    return specific_h, general_h

s_final, g_final = learn(concepts, target)

print("\nThe Final Specific Hypothesis:")
print(s_final)
print("\nThe Final General Hypothesis:")
print(g_final)