Create utils/plotting.py

utils/plotting.py

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+# utils/plotting.py
+
+import matplotlib.pyplot as plt
+import matplotlib.dates as mdates
+
+def plot_stock_data_with_signals(data):
+    """
+    Plots stock data, indicators, and buy/sell signals.
+
+    Parameters:
+    - data (DataFrame): DataFrame containing stock 'Close' prices, indicator values, and signals.
+    """
+    # Create a new figure and set the size.
+    plt.figure(figsize=(14, 10))
+
+    # Plot closing prices and EMAs
+    ax1 = plt.subplot(311)  # 3 rows, 1 column, 1st subplot
+    data['Close'].plot(ax=ax1, color='black', lw=2., legend=True)
+    if 'EMA_Short' in data.columns and 'EMA_Long' in data.columns:
+        data[['EMA_Short', 'EMA_Long']].plot(ax=ax1, lw=1.5, legend=True)
+    ax1.set_title('Stock Price, EMAs, and Bollinger Bands')
+    ax1.fill_between(data.index, data['BB_Lower'], data['BB_Upper'], color='grey', alpha=0.3)
+    
+    # Highlight buy/sell signals
+    buy_signals = data[data['Combined_Signal'] == 'buy']
+    sell_signals = data[data['Combined_Signal'] == 'sell']
+    ax1.plot(buy_signals.index, data.loc[buy_signals.index]['Close'], '^', markersize=10, color='g', lw=0, label='Buy Signal')
+    ax1.plot(sell_signals.index, data.loc[sell_signals.index]['Close'], 'v', markersize=10, color='r', lw=0, label='Sell Signal')
+    ax1.legend()
+
+    # Plot MACD and Signal Line
+    ax2 = plt.subplot(312, sharex=ax1)  # Share x-axis with ax1
+    data['MACD'].plot(ax=ax2, color='blue', label='MACD', legend=True)
+    data['MACD_Signal_Line'].plot(ax=ax2, color='red', label='Signal Line', legend=True)
+    ax2.fill_between(data.index, data['MACD'] - data['MACD_Signal_Line'], color='grey', alpha=0.3)
+    ax2.set_title('MACD')
+
+    # Plot RSI
+    ax3 = plt.subplot(313, sharex=ax1)  # Share x-axis with ax1
+    data['RSI'].plot(ax=ax3, color='purple', legend=True)
+    ax3.axhline(70, linestyle='--', alpha=0.5, color='red')
+    ax3.axhline(30, linestyle='--', alpha=0.5, color='green')
+    ax3.set_title('RSI')
+
+    # Improve layout and x-axis date format
+    plt.tight_layout()
+    plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
+    plt.gca().xaxis.set_major_locator(mdates.DayLocator())
+    plt.xticks(rotation=45)
+
+    plt.show()
+
+# Note: This is a basic example for visualization. You may need to adjust it based on your actual 'data' DataFrame structure and the specific indicators you are plotting.