utils/plotting.py

# 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.