Code Editor for app.py

import streamlit as st
import pandas as pd
from datetime import datetime
import plotly.express as px
import plotly.graph_objects as go

st.title("Gold Investment Calculator")

# Input section
col1, col2 = st.columns(2)

with col1:
    gold_tola = st.number_input("Amount of gold bought (in tolas)", min_value=0.0, value=1.0)
    purchase_date = st.date_input("Date when bought", value=datetime.now())
    purchase_price = st.number_input("Price per tola when bought (in your currency)", min_value=0.0, value=100000.0)

with col2:
    current_price = st.number_input("Current price per tola (in your currency)", min_value=0.0, value=120000.0)
    current_date = st.date_input("Current date", value=datetime.now())

if st.button("Calculate"):
    # Basic calculations
    total_investment = gold_tola * purchase_price
    current_value = gold_tola * current_price
    total_profit = current_value - total_investment

    # Calculate days and months between dates
    days_diff = (current_date - purchase_date).days
    months_diff = days_diff / 30.44  # average month length

    # Calculate averages
    daily_profit = total_profit / days_diff if days_diff > 0 else 0
    monthly_profit = total_profit / months_diff if months_diff > 0 else 0

    # Display results
    st.header("Investment Analysis")
    
    metrics_col1, metrics_col2, metrics_col3 = st.columns(3)
    
    with metrics_col1:
        st.metric("Total Profit", f"{total_profit:,.2f}")
    with metrics_col2:
        st.metric("Average Monthly Earning", f"{monthly_profit:,.2f}")
    with metrics_col3:
        st.metric("Average Daily Earning", f"{daily_profit:,.2f}")

    # Create date range for plotting
    date_range = pd.date_range(start=purchase_date, end=current_date)
    
    # Create daily earnings dataframe
    daily_df = pd.DataFrame({
        'Date': date_range,
        'Earnings': [daily_profit] * len(date_range)
    })

    # Create monthly earnings dataframe
    monthly_df = daily_df.set_index('Date').resample('M').sum().reset_index()

    # Plotting
    st.subheader("Daily Earnings Trend")
    fig_daily = px.line(daily_df, x='Date', y='Earnings', 
                       title='Daily Earnings Over Time')
    st.plotly_chart(fig_daily)

    st.subheader("Monthly Earnings Trend")
    fig_monthly = px.bar(monthly_df, x='Date', y='Earnings',
                        title='Monthly Earnings Over Time')
    st.plotly_chart(fig_monthly)

    # Additional investment details
    st.subheader("Investment Details")
    details_col1, details_col2 = st.columns(2)
    
    with details_col1:
        st.write("Investment Duration:")
        st.write(f"Days: {days_diff}")
        st.write(f"Months: {months_diff:.1f}")
        
    with details_col2:
        st.write("Investment Values:")
        st.write(f"Initial Investment: {total_investment:,.2f}")
        st.write(f"Current Value: {current_value:,.2f}")