Update app.py

app.py

@@ -1,3 +1,5 @@
+# app.py
+
 import streamlit as st
 from data_fetcher.yfinance_client import fetch_intraday_data
 from indicators.ema import calculate_ema
@@ -8,48 +10,53 @@ from signals.strategy import generate_combined_signals
 from utils.plotting import plot_stock_data_with_signals
 import pandas as pd
 
-# Streamlit app title
-st.title('Stock Intraday Signal App')
+# Streamlit app title with emoji
+st.title('Stock Intraday Signal App 📈')
 
-# Introduction and instructions
+# Introduction and instructions with emojis
 st.write("""
-## Introduction
-Welcome to the Stock Intraday Signal App! This application analyzes stock data to generate buy/sell signals based on technical indicators such as EMA, RSI, MACD, and Bollinger Bands. It's designed to help day traders make informed decisions.
+## Introduction 🌟
+Welcome to the Stock Intraday Signal App! This application analyzes stock data to generate buy/sell signals 🚦 based on technical indicators such as EMA, RSI, MACD, and Bollinger Bands. It's designed to help day traders 📊 make informed decisions.
 
-## How to Use
-1. Enter a stock symbol in the sidebar.
-2. Choose the date range for the analysis.
-3. Click on "Analyze" to view the stock data, indicators, and signals.
+## How to Use 🛠️
+1. Enter a stock symbol in the sidebar. 📝
+2. Choose the date range for the analysis. 🗓️
+3. Click on "Analyze" to view the stock data, indicators, and signals. 🔍
 """)
 
-# Sidebar inputs
-st.sidebar.header('User Input Parameters')
+# Sidebar inputs with emojis
+st.sidebar.header('User Input Parameters 📋')
 stock_symbol = st.sidebar.text_input('Stock Symbol', value='AAPL', max_chars=5)
 start_date = st.sidebar.date_input('Start Date')
 end_date = st.sidebar.date_input('End Date')
-analyze_button = st.sidebar.button('Analyze')
+analyze_button = st.sidebar.button('Analyze 🚀')
 
 # Main functionality
 if analyze_button:
-    # Fetch stock data
-    st.write(f"Fetching data for {stock_symbol} from {start_date} to {end_date}...")
+    st.write(f"Fetching data for {stock_symbol} from {start_date} to {end_date}... 🔄")
     data = fetch_intraday_data(stock_symbol, start_date.isoformat(), end_date.isoformat())
     
     if data.empty:
-        st.error("No data found for the given parameters. Please try different dates or stock symbols.")
+        st.error("No data found for the given parameters. Please try different dates or stock symbols. ❌")
     else:
-        # Calculate indicators
-        st.write("Calculating indicators...")
+        st.write("Calculating indicators... 🔍")
         ema_periods = [20, 50]  # Example periods for EMA
-        data = calculate_ema(data, ema_periods)
-        data = calculate_rsi(data)
-        data = calculate_macd(data)
-        data = calculate_bollinger_bands(data)
+        ema_data = calculate_ema(data['Close'], ema_periods)
+        for period, ema_series in ema_data.items():
+            data[f'EMA_{period}'] = ema_series
+            
+        rsi_results = calculate_rsi(data['Close'])
+        data = data.join(rsi_results)  # Merge the RSI results back into the main DataFrame
+        
+        macd_data = calculate_macd(data['Close'])
+        data = pd.concat([data, macd_data], axis=1)
+        
+        bb_data = calculate_bollinger_bands(data['Close'])
+        data = pd.concat([data, bb_data], axis=1)
         
-        # Generate signals
-        st.write("Generating signals...")
+        st.write("Generating signals... 🚦")
         data = generate_combined_signals(data)
         
-        # Plot results
-        st.write("Visualizing data, indicators, and signals...")
+        st.write("Visualizing data, indicators, and signals... 📊")
         plot_stock_data_with_signals(data)
+