Code Editor for app.py

import streamlit as st
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

# Generate mock data function
def generate_mock_data(tickers, start_date, end_date):
    dates = pd.date_range(start=start_date, end=end_date)
    data = {}
    for ticker in tickers:
        price_data = pd.DataFrame(index=dates)
        price_data['Open'] = np.random.uniform(100, 500, len(dates))
        price_data['Close'] = price_data['Open'] + np.random.normal(0, 10, len(dates))
        price_data['High'] = price_data[['Open', 'Close']].max(axis=1) + np.random.uniform(0, 5, len(dates))
        price_data['Low'] = price_data[['Open', 'Close']].min(axis=1) - np.random.uniform(0, 5, len(dates))
        price_data['Volume'] = np.random.randint(1000, 10000, len(dates))
        data[ticker] = price_data
    return data

# Generate mock stock data
stock_tickers = ['AAPL', 'GOOGL', 'MSFT', 'AMZN', 'FB']
start_date = '2022-01-01'
end_date = '2023-01-01'
stock_data = generate_mock_data(stock_tickers, start_date, end_date)

st.title('Stock Analysis Dashboard')

# Stock Selector
selected_stock = st.selectbox('Select Stock:', stock_tickers)

# Date Range Picker
start_date = st.date_input('Start Date', pd.to_datetime('2022-01-01'))
end_date = st.date_input('End Date', pd.to_datetime('2023-01-01'))

# Filter data based on date range
stock_df = stock_data[selected_stock].loc[start_date:end_date]

# Plotting
st.subheader(f'{selected_stock} Price Trend')
chart_type = st.radio('Chart Type:', ['Line', 'Bar'])

if chart_type == 'Line':
    st.line_chart(stock_df[['Open', 'Close', 'High', 'Low']])
else:
    # Bar chart
    fig, ax = plt.subplots()
    stock_df[['Open', 'Close', 'High', 'Low']].plot(kind='bar', ax=ax)
    st.pyplot(fig)

# Basic Stats
st.subheader('Basic Statistics')
mean_price = stock_df['Close'].mean()
volatility = stock_df['Close'].std()

st.write(f'Mean Price: ${mean_price:.2f}')
st.write(f'Volatility: ${volatility:.2f}')

# Moving Averages
ma_period = st.number_input('MA Period:', min_value=1, max_value=30, value=5)
stock_df[f'MA_{ma_period}'] = stock_df['Close'].rolling(window=ma_period).mean()

st.line_chart(stock_df[['Close', f'MA_{ma_period}']])

# Volume Analysis
st.subheader('Volume Analysis')
st.bar_chart(stock_df['Volume'])

# Stock Comparison
st.subheader('Compare with Other Stocks')
comparison_stocks = st.multiselect('Select Other Stocks:', stock_tickers)

if comparison_stocks:
    comparison_data = stock_data[comparison_stocks]
    for comparison_stock in comparison_stocks:
        stock_data[comparison_stock].loc[start_date:end_date]['Close'].plot(label=comparison_stock)
    plt.title('Stock Comparison')
    plt.xlabel('Date')
    plt.ylabel('Price')
    plt.legend()
    st.pyplot()