Create utils/plotting.py

utils/plotting.py

@@ -0,0 +1,47 @@
+import matplotlib.pyplot as plt
+import matplotlib.dates as mdates
+
+def plot_data_with_indicators_and_signals(data):
+    """
+    Plots historical price data, SMAs, Bollinger Bands, and buy/sell signals.
+
+    Args:
+        data (pd.DataFrame): The DataFrame containing the historical prices, SMAs, Bollinger Bands,
+                             and signals. It expects 'close', 'SMA_21', 'SMA_50', 'BB_Upper',
+                             'BB_Lower', 'Buy_Signal', and 'Sell_Signal' columns.
+    """
+    # Create a new figure and set the size
+    plt.figure(figsize=(14, 7))
+
+    # Plot closing price
+    plt.plot(data['date'], data['close'], label='Close Price', alpha=0.5)
+
+    # Plot SMAs
+    plt.plot(data['date'], data['SMA_21'], label='21-Period SMA', alpha=0.75)
+    plt.plot(data['date'], data['SMA_50'], label='50-Period SMA', alpha=0.75)
+
+    # Plot Bollinger Bands
+    plt.plot(data['date'], data['BB_Upper'], label='Upper Bollinger Band', linestyle='--', alpha=0.5)
+    plt.plot(data['date'], data['BB_Lower'], label='Lower Bollinger Band', linestyle='--', alpha=0.5)
+
+    # Highlight buy signals
+    buy_signals = data[data['Buy_Signal']]
+    plt.scatter(buy_signals['date'], buy_signals['close'], label='Buy Signal', marker='^', color='green', alpha=1)
+
+    # Highlight sell signals
+    sell_signals = data[data['Sell_Signal']]
+    plt.scatter(sell_signals['date'], sell_signals['close'], label='Sell Signal', marker='v', color='red', alpha=1)
+
+    # Formatting the plot
+    plt.title('Cryptocurrency Analysis with Buy/Sell Signals')
+    plt.xlabel('Date')
+    plt.ylabel('Price')
+    plt.legend()
+    plt.grid(True)
+    plt.xticks(rotation=45)
+    plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
+    plt.gca().xaxis.set_major_locator(mdates.DayLocator(interval=5))
+
+    # Show plot
+    plt.tight_layout()
+    plt.show()