Code Editor for app.py

import streamlit as st
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from datetime import datetime, timedelta

# Generate mock stock data
def generate_mock_data(tickers, start_date, end_date):
    date_range = pd.date_range(start_date, end_date)
    data = {}
    for ticker in tickers:
        prices = np.random.rand(len(date_range)) * 100
        data[ticker] = pd.DataFrame({
            'Date': date_range,
            'Open': prices,
            'Close': prices + (np.random.rand(len(date_range)) - 0.5) * 10,
            'High': prices + np.random.rand(len(date_range)) * 5,
            'Low': prices - np.random.rand(len(date_range)) * 5,
            'Volume': np.random.randint(1000, 5000, len(date_range))
        }).set_index('Date')
    return data

# Define stock tickers
stock_tickers = ['AAPL', 'TSLA', 'GOOGL', 'MSFT', 'AMZN']

# Generate mock data for the past year
end_date = datetime.now()
start_date = end_date - timedelta(days=365)
mock_data = generate_mock_data(stock_tickers, start_date, end_date)

# Streamlit app
st.title('Stock Analysis App')

# Stock selector
selected_stock = st.selectbox('Select a stock:', stock_tickers)

df = mock_data[selected_stock]

# Date range picker
start, end = st.date_input('Select date range:', [start_date, end_date])
filtered_df = df[(df.index >= pd.to_datetime(start)) & (df.index <= pd.to_datetime(end))]

# Chart type toggle
chart_type = st.selectbox('Select chart type:', ['Line', 'Bar'])

# Plotting
plt.figure(figsize=(10, 5))
if chart_type == 'Line':
    plt.plot(filtered_df.index, filtered_df['Close'], label='Close Price')
else:
    plt.bar(filtered_df.index, filtered_df['Close'], label='Close Price')
plt.title(f'{selected_stock} Price Trend')
plt.xlabel('Date')
plt.ylabel('Price')
plt.legend()
plt.grid()
st.pyplot(plt)

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

# Moving averages
moving_avg_period = st.number_input('Moving average period:', min_value=1, value=30)
df['Moving_Average'] = df['Close'].rolling(window=moving_avg_period).mean()
st.line_chart(df[['Close', 'Moving_Average']].loc[filtered_df.index])

# Volume analysis
st.bar_chart(filtered_df['Volume'])

# Stock comparison
comparison_tickers = st.multiselect('Select stocks for comparison:', stock_tickers, default=[selected_stock])
comparison_data = pd.concat([mock_data[ticker]['Close'].loc[filtered_df.index] for ticker in comparison_tickers], axis=1)
comparison_data.columns = comparison_tickers
st.line_chart(comparison_data)