| import streamlit as st | |
| import pandas as pd | |
| from model import fetch_data, calculate_indicators, calculate_support_resistance, predict_future_prices | |
| from visualizations import ( | |
| plot_stock_price, plot_predictions, plot_technical_indicators, plot_risk_levels, | |
| plot_feature_importance, plot_candlestick, plot_volume, plot_moving_averages, | |
| plot_feature_correlations | |
| ) | |
| def sidebar(): | |
| st.sidebar.title("Stock Analysis Dashboard") | |
| ticker = st.sidebar.text_input("Enter Stock Ticker Symbol:", value='SBILIFE.NS') | |
| start_date = st.sidebar.date_input("Start Date", value=pd.to_datetime('2021-01-01')) | |
| end_date = st.sidebar.date_input("End Date", value=pd.to_datetime('2024-09-01')) | |
| algorithm = st.sidebar.selectbox("Select Prediction Algorithm", ['Linear Regression', 'ARIMA','Decision Tree', 'Random Forest', 'XGBoost', 'CatBoost', 'LSTM', 'SARIMA']) | |
| return ticker, start_date, end_date, algorithm | |
| def display_analysis(data, algorithm): | |
| if data is not None: | |
| try: | |
| support_price, resistance_price = calculate_support_resistance(data) | |
| future_prices, mae, r2, accuracy, conf_matrix = predict_future_prices(data, algorithm) | |
| if future_prices is not None: | |
| st.write("### Technical Indicators") | |
| indicators = { | |
| 'SMA_50': data['SMA_50'].iloc[-1], | |
| 'EMA_50': data['EMA_50'].iloc[-1], | |
| 'RSI': data['RSI'].iloc[-1], | |
| 'MACD': data['MACD'].iloc[-1], | |
| 'MACD_Signal': data['MACD_Signal'].iloc[-1], | |
| 'Bollinger_High': data['Bollinger_High'].iloc[-1], | |
| 'Bollinger_Low': data['Bollinger_Low'].iloc[-1], | |
| 'ATR': data['ATR'].iloc[-1], | |
| 'OBV': data['OBV'].iloc[-1] | |
| } | |
| for key, value in indicators.items(): | |
| with st.expander(f"{key} Description"): | |
| st.write(f"{key}: {value:.2f}") | |
| st.write(get_indicator_description(key)) | |
| st.write("### Support and Resistance Levels") | |
| st.write(f"Support Price: {support_price:.2f}") | |
| st.write(f"Resistance Price: {resistance_price:.2f}") | |
| st.write("### Future Price Predictions") | |
| st.write(pd.DataFrame({'Day': range(1, len(future_prices) + 1), 'Predicted Price': future_prices})) | |
| if accuracy is not None and conf_matrix is not None: | |
| st.write(f"**Model Accuracy:** {accuracy:.2f}") | |
| st.write("**Confusion Matrix:**") | |
| st.pyplot(ConfusionMatrixDisplay(conf_matrix).plot()) | |
| if mae is not None and r2 is not None: | |
| st.write(f"**Mean Absolute Error (MAE):** {mae:.2f}") | |
| st.write(f"**R-squared (R2):** {r2:.2f}") | |
| else: | |
| st.error("Model selection or prediction failed. Please check your inputs and try again.") | |
| except Exception as e: | |
| st.error(f"An error occurred during analysis: {e}") | |
| else: | |
| st.error("Failed to fetch data. Please check the stock ticker symbol and date range.") | |
| def get_indicator_description(indicator): | |
| descriptions = { | |
| 'SMA_50': "SMA_50 (50-day Simple Moving Average): Yeh 50 din ka average hai jo bataata hai stock ka long-term trend. Agar yeh price line se upar hai, toh stock ka trend upward hai.", | |
| 'EMA_50': "EMA_50 (50-day Exponential Moving Average): Yeh bhi ek average hai lekin recent prices ko zyada weightage deta hai. Stock ka short-term trend dikhata hai.", | |
| 'RSI': "RSI (Relative Strength Index): Yeh indicator stock ke overbought ya oversold condition ko dikhata hai. 70 se zyada overbought, aur 30 se kam oversold hai.", | |
| 'MACD': "MACD: Yeh indicator short-term aur long-term moving averages ke beech ka difference dikhata hai.", | |
| 'MACD_Signal': "MACD Signal: Yeh line MACD ke signal ko dikhata hai. Jab MACD line isse cross karti hai, toh trend change hota hai.", | |
| 'Bollinger_High': "Bollinger High: Yeh line stock price ki upper boundary dikhati hai. Agar price isse upar hai, toh stock overbought ho sakta hai.", | |
| 'Bollinger_Low': "Bollinger Low: Yeh line stock price ki lower boundary dikhati hai. Agar price isse neeche hai, toh stock oversold ho sakta hai.", | |
| 'ATR': "ATR (Average True Range): Yeh indicator stock ki volatility dikhata hai. Zyada ATR matlab zyada price fluctuations.", | |
| 'OBV': "OBV (On-Balance Volume): Yeh volume aur price ke relationship ko dikhata hai. Jab OBV badh raha hai, toh stock ka demand badh raha hai." | |
| } | |
| return descriptions.get(indicator, "Description not available") | |
| def display_visualizations(data, algorithm): | |
| if data is not None: | |
| choice = st.sidebar.selectbox( | |
| "Choose a type of visualization", | |
| [ | |
| "Stock Price", | |
| "Predictions vs Actual", | |
| "Technical Indicators", | |
| "Risk Levels", | |
| "Feature Importance", | |
| "Candlestick", | |
| "Volume", | |
| "Moving Averages", | |
| "Feature Correlations" | |
| ] | |
| ) | |
| try: | |
| if choice == "Stock Price": | |
| plot_stock_price(data) | |
| elif choice == "Predictions vs Actual": | |
| future_prices, _, _, _, _ = predict_future_prices(data, algorithm) | |
| if future_prices is not None: | |
| st.line_chart(pd.DataFrame({'Actual Prices': data['Close'], 'Predicted Prices': pd.Series(future_prices).values})) | |
| else: | |
| st.error("Failed to fetch predictions.") | |
| elif choice == "Technical Indicators": | |
| indicators = { | |
| 'SMA_50': data['SMA_50'], | |
| 'EMA_50': data['EMA_50'], | |
| 'RSI': data['RSI'], | |
| 'MACD': data['MACD'], | |
| 'MACD_Signal': data['MACD_Signal'], | |
| 'Bollinger_High': data['Bollinger_High'], | |
| 'Bollinger_Low': data['Bollinger_Low'], | |
| 'ATR': data['ATR'], | |
| 'OBV': data['OBV'] | |
| } | |
| plot_technical_indicators(data, indicators) | |
| elif choice == "Risk Levels": | |
| plot_risk_levels(data) | |
| elif choice == "Feature Importance": | |
| plot_feature_importance() | |
| elif choice == "Candlestick": | |
| plot_candlestick(data) | |
| elif choice == "Volume": | |
| plot_volume(data) | |
| elif choice == "Moving Averages": | |
| plot_moving_averages(data) | |
| elif choice == "Feature Correlations": | |
| plot_feature_correlations(data) | |
| except Exception as e: | |
| st.error(f"An error occurred during visualization: {e}") | |
| else: | |
| st.error("Failed to fetch data. Please check the stock ticker symbol and date range.") | |