umer6016
Initial commit: End-to-End Stock Prediction System
3bce488
import pandas as pd
import matplotlib.pyplot as plt
import os
def perform_eda(file_path: str, output_dir: str = "reports/eda"):
"""
Generates EDA plots for the given stock data.
"""
df = pd.read_csv(file_path)
df['timestamp'] = pd.to_datetime(df['timestamp'])
df = df.sort_values('timestamp')
os.makedirs(output_dir, exist_ok=True)
# Plot 1: Close Price with SMA
plt.figure(figsize=(14, 7))
plt.plot(df['timestamp'], df['close'], label='Close Price')
if 'sma_20' in df.columns:
plt.plot(df['timestamp'], df['sma_20'], label='SMA 20')
if 'sma_50' in df.columns:
plt.plot(df['timestamp'], df['sma_50'], label='SMA 50')
plt.title('Stock Price & Moving Averages')
plt.legend()
plt.savefig(f"{output_dir}/price_sma.png")
plt.close()
# Plot 2: RSI
if 'rsi' in df.columns:
plt.figure(figsize=(14, 5))
plt.plot(df['timestamp'], df['rsi'], label='RSI', color='purple')
plt.axhline(70, linestyle='--', color='red')
plt.axhline(30, linestyle='--', color='green')
plt.title('Relative Strength Index (RSI)')
plt.legend()
plt.savefig(f"{output_dir}/rsi.png")
plt.close()
print(f"EDA plots saved to {output_dir}")
if __name__ == "__main__":
# Example usage
# perform_eda("data/processed/AAPL_processed.csv")
pass