Dataset: S&P 500 Companies With Financial Information

About this Dataset

S&P 500 Companies With Financial Information

Context

This is a comprehensive dataset including numerous financial metrics that many professionals and investing gurus often use to value companies. This data is a look at the companies that comprise the S&P 500 (Standard & Poor's 500). The S&P 500 is a capitalization-weighted index of the top 500 publicly traded companies in the United States (top 500 meaning the companies with the largest market cap). The S&P 500 index is a useful index to study because it generally reflects the health of the overall U.S. stock market. The dataset was last updated in July 2020.

Content

There are 14 rows included in this dataset:

- 4 character variables:
     - Symbol: Ticker symbol used to uniquely identify each company on a particular stock market
     - Name: Legal name of the company
     - Sector: An area of the economy where businesses share a related product or service
     - SEC Filings: Helpful documents relating to a company

 - 10 numeric variables:
     - Price: Price per share of the company
     - Price to Earnings (PE): The ratio of a company’s share price to its earnings per share
     - Dividend Yield: The ratio of the annual dividends per share divided by the price per share
     - Earnings Per Share (EPS): A company’s profit divided by the number of shares of its stock
     - 52 week high and low: The annual high and low of a company’s share price
     - Market Cap: The market value of a company’s shares (calculated as share price x number of shares)
     - EBITDA: A company’s earnings before interest, taxes, depreciation, and amortization; often used as a proxy for its profitability
     - Price to Sales (PS): A company’s market cap divided by its total sales or revenue over the past year
     - Price to Book (PB): A company’s price per share divided by its book value

Acknowledgements

I found this data on the website datahub at https://datahub.io/core/s-and-p-500-companies-financials/r/1.html. All references and citations should be given to them.

Inspiration

What useful information can you gleam from this dataset? Are these fundamentals enough to predict a high-quality company? How can you determine high from low quality? What would you liked to have seen in this dataset?

Tables

Financials

@kaggle.paytonfisher_sp_500_companies_with_financial_information.financials

57.93 KB
505 rows
14 columns


CREATE TABLE financials (
  "symbol" VARCHAR,
  "name" VARCHAR,
  "sector" VARCHAR,
  "price" DOUBLE,
  "price_earnings" DOUBLE,
  "dividend_yield" DOUBLE,
  "earnings_share" DOUBLE,
  "n_52_week_low" DOUBLE,
  "n_52_week_high" DOUBLE,
  "market_cap" DOUBLE,
  "ebitda" DOUBLE,
  "price_sales" DOUBLE,
  "price_book" DOUBLE,
  "sec_filings" VARCHAR
);