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@@ -9,6 +9,7 @@ import pandas as pd from sklearn.model_selection import train_test_split from sklearn.tree import DecisionTreeClassifier import json +import openpyxl pygame.init() @@ -484,8 +485,54 @@ def choose_pizza(prefernce): clf = DecisionTreeClassifier(random_state=400) clf = clf.fit(x_train, y_train) + ans = clf.predict([prefernce]) + + append_choice(ans, prefernce, d, df) + + return ans + +def append_df_to_excel(df, excel_path): + df_excel = pd.read_excel(excel_path) + result = pd.concat([df_excel, df], ignore_index=True) + result.to_excel(excel_path, index=False) + +def append_choice(ans, pre, d, df): + new_row = pre + new_row.append(list(d.keys())[list(d.values()).index(int(ans))]) + if new_row[3] == 30: + new_row[3] = 'low' + if new_row[3] == 50: + new_row[3] = 'high' + + if new_row[4] == 0: + new_row[4] = 'none' + if new_row[4] == 1: + new_row[4] = 'tomato' + if new_row[4] == 2: + new_row[4] = 'feta' + if new_row[4] == 3: + new_row[4] = 'olives' + + if new_row[5] == 0: + new_row[5] = 'none' + if new_row[5] == 1: + new_row[5] = 'salami' + if new_row[5] == 2: + new_row[5] = 'mushrooms' + if new_row[5] == 3: + new_row[5] = 'pineapple' + if new_row[5] == 4: + new_row[5] = 'shrimps' + if new_row[5] == 5: + new_row[5] = 'sausage' + + data = {"budget": new_row[0], "spiciness": new_row[1], "vege": new_row[2], "level of hunger": new_row[3], + "allergy": new_row[4], "favorite ingridient": new_row[5], "drink in": 1, "pizza": new_row[7]} + + n_df = pd.DataFrame(data, index=[len(df) + 1]) + append_df_to_excel(n_df, "restaurant.xlsx") + - return clf.predict([prefernce]) def get_pizza(number): with open("dishes.json") as f: