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# utils/plotting.py
import matplotlib.pyplot as plt
import pandas as pd
def plot_stock_data(data, buy_signals=None, sell_signals=None, title="Stock Data with Indicators"):
"""
Plots stock data with SMAs, Bollinger Bands, and buy/sell signals.
Parameters:
- data: DataFrame containing the stock data with 'Close', 'SMA_21', 'SMA_50', 'BB_Upper', and 'BB_Lower' columns.
- buy_signals: DataFrame or Series with buy signals. Must contain a 'Date' or similar index for plotting.
- sell_signals: DataFrame or Series with sell signals. Must contain a 'Date' or similar index for plotting.
- title: Title of the plot.
"""
# Create a new figure and set the size
plt.figure(figsize=(14, 7))
# Plot the closing price
plt.plot(data.index, data['Close'], label='Close Price', color='skyblue', linewidth=2)
# Plot SMAs
plt.plot(data.index, data['SMA_21'], label='21-period SMA', color='orange', linewidth=1.5)
plt.plot(data.index, data['SMA_50'], label='50-period SMA', color='green', linewidth=1.5)
# Plot Bollinger Bands
plt.plot(data.index, data['BB_Upper'], label='Upper Bollinger Band', color='grey', linestyle='--', linewidth=1)
plt.plot(data.index, data['BB_Lower'], label='Lower Bollinger Band', color='grey', linestyle='--', linewidth=1)
# Highlight buy signals
if buy_signals is not None:
plt.scatter(buy_signals.index, data.loc[buy_signals.index]['Close'], marker='^', color='green', label='Buy Signal', alpha=1)
# Highlight sell signals
if sell_signals is not None:
plt.scatter(sell_signals.index, data.loc[sell_signals.index]['Close'], marker='v', color='red', label='Sell Signal', alpha=1)
# Customize the plot
plt.title(title)
plt.xlabel('Date')
plt.ylabel('Price')
plt.legend()
plt.grid(True)
# Show the plot
plt.show()
# Example usage:
# This assumes `data` DataFrame is already loaded with the required columns including 'Close', 'SMA_21', 'SMA_50', 'BB_Upper', 'BB_Lower'.
# `buy_signals` and `sell_signals` DataFrames/Series should have the dates of signals.
# Due to the nature of this example, actual data is not provided here. To test this function, ensure you have a DataFrame with the appropriate structure.
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