Code Editor for app.py

import streamlit as st
import pandas as pd
import numpy as np
import altair as alt
from datetime import datetime, timedelta

# Function to generate mock stock data
def generate_mock_data(stocks, start_date, end_date):
    date_range = pd.date_range(start=start_date, end=end_date, freq='B')  # Business days
    data = {}
    for stock in stocks:
        prices = np.random.uniform(low=100, high=500, size=len(date_range))
        open_prices = prices + np.random.uniform(-5, 5, size=len(date_range))
        volume = np.random.randint(1000, 10000, size=len(date_range))
        data[stock] = {
            'Date': date_range,
            'Open': open_prices,
            'Close': prices,
            'Volume': volume,
        }
    return data

# Generate mock data for 5 tech stocks
stocks = ['AAPL', 'MSFT', 'GOOGL', 'AMZN', 'FB']
start_date = (datetime.now() - timedelta(days=365)).date()
end_date = datetime.now().date()
mock_data = generate_mock_data(stocks, start_date, end_date)

# Prepare data for the selected stock
selected_stock = st.sidebar.selectbox('Select a Stock', stocks)
stock_data = pd.DataFrame(mock_data[selected_stock])

# Date range picker
start, end = st.sidebar.date_input('Date range', [start_date, end_date])
stock_data = stock_data[(stock_data['Date'] >= pd.to_datetime(start)) & (stock_data['Date'] <= pd.to_datetime(end))]

# Price trend chart
st.subheader(f'{selected_stock} Price Trend')
price_chart = alt.Chart(stock_data).mark_line().encode(
    x='Date:T',
    y='Close:Q',
    tooltip=['Date:T', 'Close:Q']
).interactive()
st.altair_chart(price_chart, use_container_width=True)

# Basic stats
mean_close = stock_data['Close'].mean()
volatility = stock_data['Close'].std()
st.write(f'Mean Close Price: ${mean_close:.2f}')
st.write(f'Volatility (Std Dev): ${volatility:.2f}')

# Moving Average
days_moving_avg = st.sidebar.slider('Select Moving Average Window (days)', 1, 30, 5)
stock_data[f'{days_moving_avg} Day MA'] = stock_data['Close'].rolling(window=days_moving_avg).mean()

# Moving average chart
moving_avg_chart = alt.Chart(stock_data).mark_line(color='orange').encode(
    x='Date:T',
    y=f'{days_moving_avg} Day MA:Q'
)
combined_chart = price_chart + moving_avg_chart
st.altair_chart(combined_chart, use_container_width=True)

# Volume analysis chart
st.subheader(f'{selected_stock} Volume Analysis')
volume_chart = alt.Chart(stock_data).mark_bar().encode(
    x='Date:T',
    y='Volume:Q',
    tooltip=['Date:T', 'Volume:Q']
).interactive()
st.altair_chart(volume_chart, use_container_width=True)

# Stock comparison feature
st.sidebar.subheader('Compare Stocks')
comparison_stocks = st.sidebar.multiselect('Select Stocks to Compare', stocks, default=[stocks[1], stocks[2]])
comparison_data = pd.DataFrame()  
for stock in comparison_stocks:
    comp_stock_data = pd.DataFrame(mock_data[stock])
    comp_stock_data = comp_stock_data[(comp_stock_data['Date'] >= pd.to_datetime(start)) & (comp_stock_data['Date'] <= pd.to_datetime(end))]
    comparison_data[stock] = comp_stock_data['Close']
comparison_data['Date'] = comp_stock_data['Date']
comparison_chart = alt.Chart(comparison_data).transform_fold(
    comparison_stocks,
    as_=['Stock', 'Price']
).mark_line().encode(
    x='Date:T',
    y='Price:Q',
    color='Stock:N'
)
st.subheader('Selected Stocks Comparison')
st.altair_chart(comparison_chart, use_container_width=True)