Unfortunately, the API this dataset used to pull the stock data isn't free anymore. Instead of having this auto-updating, I dropped the last version of the data files in here, so at least the historic data is still usable.
This dataset provides free end of day data for all stocks currently in the Dow Jones Industrial Average. For each of the 30 components of the index, there is one CSV file named by the stock's symbol (e.g. AAPL for Apple). Each file provides historically adjusted market-wide data (daily, max. 5 years back). See here for description of the columns: https://iextrading.com/developer/docs/#chart
Since this dataset uses remote URLs as files, it is automatically updated daily by the Kaggle platform and automatically represents the latest data.
List of stocks and symbols as per https://en.wikipedia.org/wiki/Dow_Jones_Industrial_Average
Thanks to https://iextrading.com for providing this data for free!
Data provided for free by IEX. View IEX’s Terms of Use.
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
According to Investopedia:
FAANG is an acronym referring to the stocks of the five most popular and best-performing American technology companies: Facebook, Amazon, Apple, Netflix and Alphabet (formerly known as Google). In addition to being widely known among consumers, the five FAANG stocks are among the largest companies in the world, with a combined market capitalization of over $4.1 trillion as of January 2020. Some have raised concerns that the FAANG stocks may be in the midst of a bubble, whereas others argue that their growth is justified by the stellar financial and operational performance they have shown in recent years.
Regardless of the myriad of accolades, comments, and even controversies surrounding the FAANG stocks, they are nevertheless a data science/mining treasure and the bellwether of the NASDAQ index, if not the entire US technology sector.
This Kaggle dataset contains over 20 years of daily historical data for the five FAANG constituents, as retrieved from this free stock API. It is a public-domain dataset that gives the data science practitioners (a.k.a., you!) the full flexibility to derive second-order insights and investment heuristics from it.
Over 20 years of daily historical data (2000-01-01 to 2020-10-01) for the five FAANG stocks: Facebook, Amazon, Apple, Netflix, and Alphabet/Google. For completeness, both raw and adjusted prices are included, along with historical split events and dividend payouts (check out here for how stock market API providers perform price adjustments).
Data source: https://www.alphavantage.co/
https://optiondata.org/about.htmlhttps://optiondata.org/about.html
Historical option EOD data in 2021, dataset files in CSV format.
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
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Data from: https://www.optionsdx.com
2010-2023 Option data for SPY EOD
If you want it to be put into one CSV file without nan's, go here:
https://www.kaggle.com/datasets/benjaminbtang/spy-options-2010-2023-eod/data
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Unfortunately, the API this dataset used to pull the stock data isn't free anymore. Instead of having this auto-updating, I dropped the last version of the data files in here, so at least the historic data is still usable.
This dataset provides free end of day data for all stocks currently in the Dow Jones Industrial Average. For each of the 30 components of the index, there is one CSV file named by the stock's symbol (e.g. AAPL for Apple). Each file provides historically adjusted market-wide data (daily, max. 5 years back). See here for description of the columns: https://iextrading.com/developer/docs/#chart
Since this dataset uses remote URLs as files, it is automatically updated daily by the Kaggle platform and automatically represents the latest data.
List of stocks and symbols as per https://en.wikipedia.org/wiki/Dow_Jones_Industrial_Average
Thanks to https://iextrading.com for providing this data for free!
Data provided for free by IEX. View IEX’s Terms of Use.