Scikit-learn-python-car.py

import pandas as pd
from sklearn import tree
import time
df=pd.read_csv('C:\\Users\\peyman\\pythonProject16\\Write_price_car_from_database_for.csv')
# print(df.head())

Miles_Car=df['Miles Car']
Year_Car=df['Year Car']
Accident_Car=df['Accident Car']
Owner_Car=df['Owner Car']
Price_Car=df['Price Car']
Name_car=df['Name Car']
Color_Exterior=df['Color Exterior']
Color_Interior=df['Color Interior']
Person_Car=df['Person Car']
Model_Car = ['Model Car']

x=[]
y=[]


for i in range(len(df)):
    x.append([Miles_Car[i],Year_Car[i],Accident_Car[i],Owner_Car[i]])
    y.append([Price_Car[i]])


y_input=2020
m_input=81
a_input=0
o_input=1
max_price=30
min_price=8

print("Please waite....")
time.sleep(5)
print()
clf = tree.DecisionTreeRegressor()
clf = clf.fit(x,y)
new_data=[[m_input, y_input, a_input, o_input]]
answer = clf.predict(new_data)
print(f'''Hello .....
The specifications of the car you want are:
Car year: {y_input}
Car operation: {m_input} Miles
Number of accidents: {a_input}
Number of owners: {o_input} person
Min Price {min_price} and Max Price: {max_price}''')
print("Please waite....")
print()
time.sleep(5)
list_answer = []
for item in answer:
    list_answer.append(item)
print("Result : ")
if list_answer[0]>=min_price and list_answer[0]<=max_price:
    df_price = df[df['Price Car'] ==list_answer[0]]
    search_price=df_price['Name Car'].tolist()
    search_color_ex=df_price['Color Exterior'].tolist()
    search_color_in = df_price['Color Interior'].tolist()
    search_model=df_price['Model Car'].tolist()
    search_person=df_price['Person Car'].tolist()
    print(f'''Name Car: {search_price[0]}   and     
Model Car : {search_model[0]}   and              
Color Exterior : {search_color_ex[0]}   and        ==> Price Car : {list_answer[0]}$
Color Interior :{search_color_in[0]} and      
Person Car : {search_person[0]}
 ''')
else:
    print(f'''We are sorry!!!!
The car is not available at the price you want
The car with the specifications you asked for is available at the price: {list_answer[0]}$''')