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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()
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