Code Editor for app.py

import streamlit as st
import pandas as pd
import numpy as np

st.title("Car Cost Comparison Calculator")

# Initialize form inputs
with st.form("car_form"):
    name = st.text_input("Name")
    vehicle_type = st.selectbox(
        "Type of vehicle",
        ["Family car not older than 2020"],
        disabled=True
    )
    financing_capabilities = st.number_input("Financing capabilities (in shekels)", min_value=0, value=50000)
    km_per_year = st.number_input("Kilometers per year", min_value=0, value=20000)
    
    # Checkboxes for comparison
    col1, col2, col3 = st.columns(3)
    with col1:
        show_leasing = st.checkbox("Leasing vehicle", value=True)
    with col2:
        show_buying = st.checkbox("Buying a car", value=True)
    with col3:
        show_operational = st.checkbox("Operational leasing", value=True)
    
    submitted = st.form_submit_button("Calculate")

if submitted:
    # Calculate costs for each option
    options = []
    costs = []
    
    if show_leasing:
        # Option A: Leasing from work
        test_treatment = 5000
        financing = max(0, (100000-financing_capabilities)) * 0.10
        monthly = 0
        initial = 100000
        insurance = 5000
        impairment = 100000 * 0.11
        fuel = km_per_year * 7.5/17
        total = test_treatment + financing + (monthly * 12) + insurance + impairment + fuel
        
        options.append("Leasing from work")
        costs.append({
            "Test & Treatments (yearly)": test_treatment,
            "Financing (yearly)": financing,
            "Monthly Payment": monthly,
            "Initial Payment": initial,
            "Insurance (yearly)": insurance,
            "Impairment Loss (yearly)": impairment,
            "Fuel (yearly)": fuel,
            "Total Yearly Costs": total
        })
    
    if show_buying:
        # Option B: Buying a car
        options.append("Buying a car")
        costs.append({
            "Test & Treatments (yearly)": 0,
            "Financing (yearly)": 0,
            "Monthly Payment": 4500,
            "Initial Payment": 0,
            "Insurance (yearly)": 0,
            "Impairment Loss (yearly)": 0,
            "Fuel (yearly)": 0,
            "Total Yearly Costs": 4500 * 12
        })
    
    if show_operational:
        # Option C: Operational leasing
        test_treatment = 1800
        financing = 0
        monthly = 2650
        initial = 1900
        insurance = 0
        impairment = 0
        fuel = km_per_year * 7.5/17
        total = test_treatment + financing + (monthly * 12) + insurance + impairment + fuel
        
        options.append("Operational leasing")
        costs.append({
            "Test & Treatments (yearly)": test_treatment,
            "Financing (yearly)": financing,
            "Monthly Payment": monthly,
            "Initial Payment": initial,
            "Insurance (yearly)": insurance,
            "Impairment Loss (yearly)": impairment,
            "Fuel (yearly)": fuel,
            "Total Yearly Costs": total
        })
    
    # Create comparison DataFrame
    df = pd.DataFrame(costs, index=options)
    
    # Display results
    st.header("Cost Comparison")
    st.dataframe(df.style.format("{:.2f}"))
    
    # Create bar chart for total yearly costs
    st.header("Total Yearly Costs Comparison")
    st.bar_chart(df["Total Yearly Costs"])
    
    # Show additional insights
    st.header("Analysis")
    min_cost_option = df["Total Yearly Costs"].idxmin()
    st.write(f"The most cost-effective option is: **{min_cost_option}**")
    
    # Calculate and display 5-year total cost
    five_year_costs = df["Total Yearly Costs"] * 5 + df["Initial Payment"]
    st.header("5-Year Total Cost Comparison")
    st.dataframe(five_year_costs.to_frame("5-Year Total Cost").style.format("{:.2f}"))