Code Editor for app.py

import streamlit as st
import pandas as pd
import numpy as np
import plotly.graph_objects as go
import plotly.express as px
from datetime import datetime, timedelta
import yfinance as yf

# Set page config
st.set_page_config(layout="wide", page_title="Financial Dashboard")

# Apply dark theme
st.markdown("""
    <style>
    .stApp {
        background-color: #0E1117;
        color: #FAFAFA;
    }
    </style>
""", unsafe_allow_html=True)

# Sidebar
with st.sidebar:
    st.title("Stock Analysis Dashboard")
    ticker_symbol = st.text_input("Enter Stock Symbol", value="AAPL")
    period = st.selectbox("Select Time Period", 
                         ["1mo", "3mo", "6mo", "1y", "2y", "5y"], 
                         index=3)

# Fetch data
@st.cache_data
def get_stock_data(symbol, period):
    stock = yf.Ticker(symbol)
    hist = stock.history(period=period)
    return hist, stock.info

df, info = get_stock_data(ticker_symbol, period)

# Main layout
col1, col2 = st.columns([2, 1])

with col1:
    # Main price chart
    fig = go.Figure()
    fig.add_trace(go.Candlestick(x=df.index,
                                open=df['Open'],
                                high=df['High'],
                                low=df['Low'],
                                close=df['Close'],
                                name='OHLC'))
    fig.update_layout(
        title=f"{ticker_symbol} Stock Price",
        yaxis_title="Stock Price (USD)",
        template="plotly_dark",
        height=400
    )
    st.plotly_chart(fig, use_container_width=True)

    # Volume chart
    volume_fig = px.bar(df, x=df.index, y='Volume', 
                       title=f"{ticker_symbol} Trading Volume")
    volume_fig.update_layout(template="plotly_dark", height=200)
    st.plotly_chart(volume_fig, use_container_width=True)

with col2:
    # Key metrics
    st.subheader("Key Metrics")
    metrics = {
        "Market Cap": info.get('marketCap', 'N/A'),
        "P/E Ratio": info.get('trailingPE', 'N/A'),
        "52 Week High": info.get('fiftyTwoWeekHigh', 'N/A'),
        "52 Week Low": info.get('fiftyTwoWeekLow', 'N/A'),
        "Dividend Yield": info.get('dividendYield', 'N/A')
    }
    
    for metric, value in metrics.items():
        col_metric, col_value = st.columns([1, 1])
        with col_metric:
            st.write(metric)
        with col_value:
            if isinstance(value, (int, float)):
                if metric == "Market Cap":
                    st.write(f"${value:,.0f}")
                elif metric == "Dividend Yield":
                    st.write(f"{value:.2%}")
                else:
                    st.write(f"{value:.2f}")
            else:
                st.write(value)

# Additional charts in lower section
col1, col2, col3 = st.columns(3)

with col1:
    # Daily returns histogram
    df['Daily Return'] = df['Close'].pct_change()
    returns_fig = px.histogram(df, x='Daily Return', 
                             title='Distribution of Daily Returns')
    returns_fig.update_layout(template="plotly_dark", height=300)
    st.plotly_chart(returns_fig, use_container_width=True)

with col2:
    # Moving averages
    df['MA20'] = df['Close'].rolling(window=20).mean()
    df['MA50'] = df['Close'].rolling(window=50).mean()
    ma_fig = go.Figure()
    ma_fig.add_trace(go.Scatter(x=df.index, y=df['Close'], 
                               name='Price', line=dict(color='white')))
    ma_fig.add_trace(go.Scatter(x=df.index, y=df['MA20'], 
                               name='20 Day MA', line=dict(color='orange')))
    ma_fig.add_trace(go.Scatter(x=df.index, y=df['MA50'], 
                               name='50 Day MA', line=dict(color='blue')))
    ma_fig.update_layout(title='Moving Averages', template="plotly_dark", height=300)
    st.plotly_chart(ma_fig, use_container_width=True)

with col3:
    # RSI calculation and plot
    delta = df['Close'].diff()
    gain = (delta.where(delta > 0, 0)).rolling(window=14).mean()
    loss = (-delta.where(delta < 0, 0)).rolling(window=14).mean()
    rs = gain / loss
    df['RSI'] = 100 - (100 / (1 + rs))
    
    rsi_fig = go.Figure()
    rsi_fig.add_trace(go.Scatter(x=df.index, y=df['RSI'], 
                                name='RSI', line=dict(color='purple')))
    rsi_fig.add_hline(y=70, line_dash="dash", line_color="red")
    rsi_fig.add_hline(y=30, line_dash="dash", line_color="green")
    rsi_fig.update_layout(title='Relative Strength Index (RSI)', 
                         template="plotly_dark", height=300)
    st.plotly_chart(rsi_fig, use_container_width=True)