Compare Stock Performance Over Multiple Time Frames with Yahoo Finance API and Matplotlib

README.md

Compare Stock Performance Over Multiple Time Frames with Yahoo Finance API and Matplotlib

How to Use

Compare the performance of a stock across two or more time frames using the Yahoo Finance API and the Matplotlib Python library. Adjust the stock symbol and time frames according to your requirements and save the content in a file named script.py.

import requests
import matplotlib.pyplot as plt
from datetime import datetime

proxy = {'http': 'http://127.0.0.1:8080','https': 'https://127.0.0.1:8080'}

def fetch_stock_data(symbol, period1, period2, interval):
    url = f'http://query1.finance.yahoo.com/v8/finance/chart/{symbol}?period1={period1}&period2={period2}&interval={interval}&includePrePost=true&events=div%7Csplit%7Cearn&useYfid=true&lang=en-US&region=US'
    headers = {
        'User-Agent': 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:125.0) Gecko/20100101 Firefox/125.0'
    }
    response = requests.get(url, headers=headers) #, proxies=proxy)
    try:
        data = response.json()
    except Exception as e:
        print("Error fetching data:", e)
        print("Response content:", response.content)
        return None
    return data

def generate_comparison_graph(data_list, timeframe_list):
    plt.figure(figsize=(12, 6))

    for i, data in enumerate(data_list):
        timestamps = data['chart']['result'][0]['timestamp']
        prices = data['chart']['result'][0]['indicators']['quote'][0]['close']
        # plt.plot(timestamps, prices, label=f'BSE SENSEX ({timeframe_list[i]})')
        plt.plot(prices, label=f'BSE SENSEX ({timeframe_list[i]})')

    #plt.xlabel('Date')
    plt.ylabel('Price')
    plt.title('BSE SENSEX Prices Comparison')
    plt.legend()
    plt.show()

def main():
    symbol = '^BSESN'

    # Define the timeframes
    timeframes = [
        ('1999-10-06', '2004-05-12'),
        ('2004-05-13', '2009-05-15'),
        ('2009-05-16', '2014-05-15'),
        ('2014-05-16', '2019-05-22'),
        ('2019-05-23', '2024-04-29')
    ]
    interval = '1d'  # Daily interval

    # Convert timeframes to Unix timestamps and fetch data
    data_list = []
    timeframe_list = []
    for start_date, end_date in timeframes:
        period1 = int(datetime.strptime(start_date, '%Y-%m-%d').timestamp())
        period2 = int(datetime.strptime(end_date, '%Y-%m-%d').timestamp())
        data = fetch_stock_data(symbol, period1, period2, interval)
        data_list.append(data)
        timeframe_list.append(f"{start_date} to {end_date}")

    # Generate comparison graph
    generate_comparison_graph(data_list, timeframe_list)

if __name__ == "__main__":
    main()

Execute the script using the python3 script.py command:

bipin@bipin-VirtualBox:~$ python3 script.py

Upon successful execution, the script will display the graph as shown below. Please note, pictures of politicians are not included; those are added by me. ;)

Data:

Here's the dates I used:

Election Dates	Result Declaration Dates	Oath Date	PM Name - Party in Power	Tenure	Majority Seats
5 Sep - 3 Oct 1999	6 Oct 1999	13 Oct 1999	Atal Bihari Vajpayee - BJP (NDA)	13 Oct 1999 - 22 May 2004	182
20 Apr - 10 May 2004	13 May 2004	22 May 2004	Manmohan Singh - INC (UPA)	22 May 2004 - 26 May 2014	145
16 Apr - 13 May 2009	16 May 2009	22 May 2009	Manmohan Singh - INC (UPA)	22 May 2009 - 26 May 2014	206
7 Apr - 12 May 2014	16 May 2014	26 May 2014	Narendra Modi - BJP (NDA)	26 May 2014 - Present	282
11 Apr - 19 May 2019	23 May 2019	30 May 2019	Narendra Modi - BJP (NDA)	30 May 2019 - Present	303
19 Apr - 1 June 2024	4 June 2024