nowe dane zapisywane do excel
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restaurant.xlsx
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restaurant.xlsx
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49
tiles.py
49
tiles.py
@ -9,6 +9,7 @@ import pandas as pd
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from sklearn.model_selection import train_test_split
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from sklearn.tree import DecisionTreeClassifier
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import json
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import openpyxl
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pygame.init()
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@ -484,8 +485,54 @@ def choose_pizza(prefernce):
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clf = DecisionTreeClassifier(random_state=400)
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clf = clf.fit(x_train, y_train)
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ans = clf.predict([prefernce])
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append_choice(ans, prefernce, d, df)
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return ans
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def append_df_to_excel(df, excel_path):
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df_excel = pd.read_excel(excel_path)
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result = pd.concat([df_excel, df], ignore_index=True)
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result.to_excel(excel_path, index=False)
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def append_choice(ans, pre, d, df):
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new_row = pre
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new_row.append(list(d.keys())[list(d.values()).index(int(ans))])
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if new_row[3] == 30:
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new_row[3] = 'low'
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if new_row[3] == 50:
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new_row[3] = 'high'
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if new_row[4] == 0:
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new_row[4] = 'none'
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if new_row[4] == 1:
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new_row[4] = 'tomato'
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if new_row[4] == 2:
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new_row[4] = 'feta'
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if new_row[4] == 3:
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new_row[4] = 'olives'
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if new_row[5] == 0:
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new_row[5] = 'none'
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if new_row[5] == 1:
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new_row[5] = 'salami'
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if new_row[5] == 2:
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new_row[5] = 'mushrooms'
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if new_row[5] == 3:
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new_row[5] = 'pineapple'
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if new_row[5] == 4:
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new_row[5] = 'shrimps'
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if new_row[5] == 5:
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new_row[5] = 'sausage'
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data = {"budget": new_row[0], "spiciness": new_row[1], "vege": new_row[2], "level of hunger": new_row[3],
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"allergy": new_row[4], "favorite ingridient": new_row[5], "drink in": 1, "pizza": new_row[7]}
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n_df = pd.DataFrame(data, index=[len(df) + 1])
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append_df_to_excel(n_df, "restaurant.xlsx")
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return clf.predict([prefernce])
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def get_pizza(number):
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with open("dishes.json") as f:
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