# Created: 20250104

import pyutil as pyu
pyu.get_local_pyinfo()

'conda env: ml312-2024; pyv: 3.12.7 | packaged by Anaconda, Inc. | (main, Oct  4 2024, 13:27:36) [GCC 11.2.0]'

print(pyu.ps2("yfinance pandas matplotlib"))

yfinance==0.2.51
pandas==2.2.3
matplotlib==3.9.3

import yfinance as yf
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

# Step 2: Calculate Rate of Change (ROC)
def calculate_roc(data, period=14):
    data['ROC'] = ((data['Close'] - data['Close'].shift(period)) / data['Close'].shift(period)) * 100
    return data

def show_graph(symbol):

    # Step 1: Download historical data
    start = "2020-01-01"
    end = "2023-12-31"
    data = yf.download(symbol, start=start, end=end)

    # Apply ROC calculation
    data = calculate_roc(data)

    # Step 3: Plot Close Price and ROC
    plt.figure(figsize=(14, 7))

    # Plot Close Price
    plt.subplot(2, 1, 1)
    plt.plot(data['Close'], label='Close Price', color='blue')
    plt.title(f'{symbol} Close Price')
    plt.xlabel('Date')
    plt.ylabel('Price')
    plt.legend()
    plt.grid(True)

    # Plot ROC
    plt.subplot(2, 1, 2)
    plt.plot(data['ROC'], label='Rate of Change (ROC)', color='purple', linewidth=1.5)
    plt.axhline(0, color='black', linestyle='--', linewidth=1, label='Zero Line')
    plt.title(f'Rate of Change (ROC) for {symbol}')
    plt.xlabel('Date')
    plt.ylabel('ROC (%)')
    plt.legend(loc='best')
    plt.grid(True)

    plt.tight_layout()
    plt.show()

show_graph("AMZN")

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