Stock Market Data And Analysis In Python – Part III

See Part I for instructions on how to get pandas_datareader or yfinance module to retrieve the data and Part II to learn how to get stock market data for different geographies.

S&P 500 Stock Tickers

If you want to analyse the stock market data for all the stocks which make up the S&P 500 then the below code will help you. It gets the list of stocks from the Wikipedia page and then fetches the stock market data from Yahoo Finance.

# Import packages
import yfinance as yf
import pandas as pd

# Read and print the stock tickers that make up S&P500
tickers = pd.read_html(
    'https://en.wikipedia.org/wiki/List_of_S%26P_500_companies')[0]
print(tickers.head())

# Get the data for this tickers from yahoo finance
data = yf.download(tickers.Symbol.to_list(),'2021-1-1','2021-7-12', auto_adjust=True)['Close']
print(data.head())

SP500_tickers_data.py hosted with ❤ by GitHub

Intraday or Minute Frequency Stock Data

yfinance module can be used to fetch the minute level stock market data. It returns the stock market data for the last 7 days.

If yfinance is not installed on your computer, then run the below line of code from your Jupyter Notebook to install yfinance.

!pip install yfinance

install yfinance.py hosted with ❤ by GitHub

The yfinance module has the download method which can be used to download the stock market data.

It takes the following parameters:

1. ticker: The name of the tickers you want the stock market data for. If you want stock market data for multiple tickers then separate them by space
2. period: The number of days/month of stock market data required. The valid frequencies are 1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max
3. interval: The frequency of the stock market data. The valid intervals are 1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo

The below code fetches the stock market data for MSFT for the past 5 days of 1-minute frequency.

import yfinance as yf
intraday_data = yf.download(tickers="MSFT",
                            period="5d",
                            interval="1m",
                            auto_adjust=True)
intraday_data.head()

minute_data.py hosted with ❤ by GitHub

Stay tuned for next installment in which Ishan Shah will show how to resample Stock Data.

See https://blog.quantinsti.com/stock-market-data-analysis-python/ for additional insight on this topic.

Past performance is not indicative of future results.

Any stock, options or futures symbols displayed are for illustrative purposes only and are not intended to portray recommendations.