Main.py

import matplotlib.pyplot as plt
from streamlit_option_menu import option_menu
import streamlit as st
import pandas as pd
from sklearn.metrics import r2_score
from sklearn.linear_model import LinearRegression
from sklearn.preprocessing import LabelEncoder
from sklearn.model_selection import train_test_split

df = pd.read_csv("FuelConsumptionCo2.csv")
file1 = "data.csv"

lt = LabelEncoder()
df['VEHICLECLASS'] = lt.fit_transform(df['VEHICLECLASS'])
df['TRANSMISSION'] = lt.fit_transform(df['TRANSMISSION'])
df['FUELTYPE'] = lt.fit_transform(df['FUELTYPE'])

x = df.drop(['MODELYEAR', 'MAKE', 'MODEL', 'FUELCONSUMPTION_CITY', 'FUELCONSUMPTION_HWY', 'FUELCONSUMPTION_COMB',
             'FUELCONSUMPTION_COMB_MPG'], axis=1)
y = df[['FUELCONSUMPTION_CITY', 'FUELCONSUMPTION_HWY', 'FUELCONSUMPTION_COMB']]

xtrain, xtest, ytrain, ytest = train_test_split(x, y, test_size=0.2, random_state=120)

lg = LinearRegression()
lg.fit(xtrain, ytrain)

with st.sidebar:
    selected = option_menu("Menu",["Home","Project","Login","SignUp","Dataset"],default_index=0)

if selected=="Project":
    vehicle_class = st.selectbox("Vehicle Class", options=sorted(df['VEHICLECLASS'].unique()))
    engine_size = st.number_input("Engine Size", min_value=0.0, value=1.0)
    cylinders = st.number_input("Number of Cylinders", min_value=1, value=4)
    transmission = st.selectbox("Transmission", options=sorted(df['TRANSMISSION'].unique()))
    fuel_type = st.selectbox("Fuel Type", options=sorted(df['FUELTYPE'].unique()))
    co2 = st.text_input("CO2Emissions")

    st.write("0.Compact 1.Full-Size 2.mid-size 3.mini-compact 4.Minivan 5.Pickup Truck Small 6.Pickup Truck Standard 7.Special Purpose Vehicle 8.Station Wagon Mid-size 9.Station Wagon Small 10.SubCompact 11.Suv-SmALL 12.Suv-Standard 13.Two-Seater 14.Van Cargo 15.Van Passenger")
    st.write("0.A4 1.A5 2.A6 3.A7 4.A8 5.A9 6.AM5 7.AM6 8.AM7 9.AS4 10.AS5 11.AS6 12.AS7 13.AS8 14.AS9 15.AV 16.AV6 17.AV7 18.AV8 19.M5 20.M6")
    st.write("D=0 , E=1 , X=2 , Z=3")

    user_data = pd.DataFrame([[vehicle_class, engine_size, cylinders, transmission, fuel_type, co2]])

    if st.button('Predict'):
        prediction = lg.predict(user_data)

        st.subheader("Predictions")
        st.write("Fuel Consumption in City:", round(prediction[0][0], 2))
        st.write("Fuel Consumption on Highway:", round(prediction[0][1], 2))
        st.write("Combined Fuel Consumption:", round(prediction[0][2], 2))

elif selected=="Login":
    st.header("Login Form")
    with st.form(key='form1'):
        email = st.text_input("Enter Email :")
        password = st.text_input("Enter password :", type='password')
        submit = st.form_submit_button(label="Submit")

        if submit:
            lines = []
            try:
                with open(file1, mode='r') as file:
                    lines = file.readlines()
            except FileNotFoundError:
                pass

            found = False
            if lines:
                for line in lines[1:]:  # Skip the header row
                    stored_email, stored_password = line.strip().split(',', 1)
                    if email == stored_email and password == stored_password:
                        st.success("Welcome, user!")
                        found = True
                        break

            if not found:
                st.error("Email and password do not exist.")

elif selected=="SignUp":
    st.header("Sign Up Form")
    with st.form(key='form2'):
        firstname = st.text_input("Enter first name:")
        lastname = st.text_input("Enter Last name:")
        age = st.number_input("Enter your age:")
        dob = st.date_input("Enter your DOB:")
        tech = st.multiselect("Select your Tech:", ['Python', 'ML', 'Django'])
        email = st.text_input("Enter Email :")
        password = st.text_input("Enter Password :",type='password')
        submit = st.form_submit_button(label='Submit')

    if submit:
        data = [[firstname,lastname,age,dob,tech,email,password]]

        with open(file1, mode='a', newline='') as file:
            file.seek(0, 2)
            if file.tell() == 0:
                file.write('First Name,Last Name,Age,Date of Birth,Technologies,Email,Password\n')

                st.write(f"**First Name:** {firstname}")
                st.write(f"**Last Name:** {lastname}")
                st.write(f"**Age:** {age}")
                st.write(f"**Date of Birth:** {dob}")
                st.write(f"**Technologies:** {', '.join(tech)}")
                st.write(f"**Email:** {email}")
                st.write(f"**Password:** (hidden for security)")

                st.success("Data saved successfully.")

elif selected=="Dataset":
    st.header("Dataset")
    data =pd.read_csv("FuelConsumptionCo2.csv")
    st.dataframe(data,width=1000)

elif selected=="Home":
    st.header("Home Page")
    st.subheader("Welcome to Home Page")
    st.write("Project info")

lg_predictions = lg.predict(xtest)
plt.scatter(ytest,lg_predictions,color='red')
plt.xlabel("True Values")
plt.ylabel("Predictions")
plt.grid(True)
plt.show()