Dataset: Fundamental Stock Data

About this Dataset

Fundamental Stock Data

It is not so often that one can find fundamental data of companies on which it would be possible to accurately assess the value of a company.

So I decided to use yahoo_fin api to collect some fundamentals of 48 companies from the S&P 500 index.

The content of indicators in each table:

total assets.
cash.
stockholder equity.
profit.
revenue.
return on equity, return on assets, profit margin.
trailing P/E, P/S, P/B, PEG, forward P/E.

In addition, the dataset has prices for all stocks for four years.

Tables

Data Assets

@kaggle.artemburenok_fundamental_stock_data.data_assets

5.7 KB
46 rows
5 columns


CREATE TABLE data_assets (
  "unnamed_0" VARCHAR,
  "n_2022" DOUBLE,
  "n_2021" DOUBLE,
  "n_2020" DOUBLE,
  "n_2019" DOUBLE
);

Data Cash

@kaggle.artemburenok_fundamental_stock_data.data_cash

5.59 KB
46 rows
5 columns


CREATE TABLE data_cash (
  "unnamed_0" VARCHAR,
  "n_2022" DOUBLE,
  "n_2021" DOUBLE,
  "n_2020" DOUBLE,
  "n_2019" DOUBLE
);

Data Equity

@kaggle.artemburenok_fundamental_stock_data.data_equity

5.69 KB
46 rows
5 columns


CREATE TABLE data_equity (
  "unnamed_0" VARCHAR,
  "n_2022" DOUBLE,
  "n_2021" DOUBLE,
  "n_2020" DOUBLE,
  "n_2019" DOUBLE
);

Data Profit

@kaggle.artemburenok_fundamental_stock_data.data_profit

5.63 KB
46 rows
5 columns


CREATE TABLE data_profit (
  "unnamed_0" VARCHAR,
  "n_2022" BIGINT,
  "n_2021" BIGINT,
  "n_2020" BIGINT,
  "n_2019" BIGINT
);

Data Revenue

@kaggle.artemburenok_fundamental_stock_data.data_revenue

5.65 KB
46 rows
5 columns


CREATE TABLE data_revenue (
  "unnamed_0" VARCHAR,
  "n_2022" BIGINT,
  "n_2021" BIGINT,
  "n_2020" BIGINT,
  "n_2019" BIGINT
);

Data Stats

@kaggle.artemburenok_fundamental_stock_data.data_stats

4.78 KB
48 rows
4 columns


CREATE TABLE data_stats (
  "unnamed_0" VARCHAR,
  "return_on_equity" DOUBLE,
  "return_on_assets" DOUBLE,
  "profit_margin" DOUBLE
);

Data Valuation

@kaggle.artemburenok_fundamental_stock_data.data_valuation

6.3 KB
48 rows
6 columns


CREATE TABLE data_valuation (
  "unnamed_0" VARCHAR,
  "trailing_p_e" DOUBLE,
  "price_sales" DOUBLE,
  "price_book" DOUBLE,
  "peg" DOUBLE,
  "forward_p_e" DOUBLE
);

Stocks

@kaggle.artemburenok_fundamental_stock_data.stocks

365.95 KB
1007 rows
49 columns


CREATE TABLE stocks (
  "unnamed_0" BIGINT,
  "date" TIMESTAMP,
  "msft" DOUBLE,
  "amzn" DOUBLE,
  "tsla" DOUBLE,
  "googl" DOUBLE,
  "goog" DOUBLE,
  "unh" DOUBLE,
  "jnj" DOUBLE,
  "xom" DOUBLE,
  "jpm" DOUBLE,
  "meta" DOUBLE,
  "v" DOUBLE,
  "pg" DOUBLE,
  "nvda" DOUBLE,
  "hd" DOUBLE,
  "cvx" DOUBLE,
  "lly" DOUBLE,
  "ma" DOUBLE,
  "abbv" DOUBLE,
  "pfe" DOUBLE,
  "mrk" DOUBLE,
  "pep" DOUBLE,
  "bac" DOUBLE,
  "ko" DOUBLE,
  "cost" DOUBLE,
  "avgo" DOUBLE,
  "tmo" DOUBLE,
  "wmt" DOUBLE,
  "csco" DOUBLE,
  "mcd" DOUBLE,
  "acn" DOUBLE,
  "abt" DOUBLE,
  "dis" DOUBLE,
  "dhr" DOUBLE,
  "wfc" DOUBLE,
  "bmy" DOUBLE,
  "lin" DOUBLE,
  "nee" DOUBLE,
  "txn" DOUBLE,
  "adbe" DOUBLE,
  "vz" DOUBLE,
  "cmcsa" DOUBLE,
  "pm" DOUBLE,
  "cop" DOUBLE,
  "amgn" DOUBLE,
  "rtx" DOUBLE,
  "hon" DOUBLE,
  "crm" DOUBLE
);