Update

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.

Content

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.

Acknowledgements

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!

Terms of Use

Data provided for free by IEX. View IEX’s Terms of Use.

View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

Tracking United HealthCare Stock Performance Since IPO

Dataset Description

This dataset provides historical stock data for UnitedHealth Group (UHG), one of the largest healthcare and insurance companies in the world. It covers stock prices, market capitalization, and trading volumes from the company's IPO to the present. As a Fortune 500 company with a significant market presence, analyzing UHG's stock performance can provide valuable insights into healthcare market trends, investment opportunities, and economic indicators.

Dataset Features

• Date – The trading date for the stock data.
• Open Price – Stock price at market open.
• Close Price – Stock price at market close.
• High – Highest stock price during the trading day.
• Low – Lowest stock price during the trading day.
• Volume – The number of shares traded on that day.
• Market Cap – The total market capitalization of UnitedHealth Group.

Dataset Distribution

• Data Volume: Number of records depends on trading days from IPO to present.
• Format: CSV, Excel, or other structured data formats.
• Update Frequency: Weekly.

Usage

This dataset is useful for:

• Stock Market Analysis – Analyzing historical stock price trends.
• Financial Forecasting – Predicting future stock price movements using machine learning.
• Investment Research – Assessing UnitedHealth Group’s stock as part of a portfolio.
• Market Trends – Understanding broader trends in the healthcare insurance sector.

Coverage

• Geographic Coverage: United States (NYSE).
• Time Range: From IPO to present.
• Economic Indicators: Healthcare sector, insurance market trends.

License

CC0 (Public Domain) – This dataset is freely available for public and commercial use.

Who Can Use This Dataset?

• Investors & Traders – To analyze market trends and make informed decisions.
• Economists & Researchers – To study healthcare market impacts.
• Data Scientists – To develop predictive stock models.

This data is downloaded from the official Bombay Stock Exchange Website (BSE). This file contains the last 10 years of Historical Stock Price (By Security & Period) Security Name - Nestle India Ltd. Period - Daily Start Date - 2nd January 2012 End Date - 21st April 2022. This is one of the Best datasets for Regression Supervised Machine Learning. You can Perform SImple as well as Multiple Linear Regression on this Dataset.

Get Nasdaq real-time and historical data with support for fast market replay at over 19 million book updates per second. Test our data for free with only 4 lines of code.

Nasdaq TotalView-ITCH is a proprietary data feed that disseminates full order book depth and last sale data from the Nasdaq stock market (XNAS). It delivers every quote and order at each price level, along with any event that updates the order book after an order is placed, such as trade executions, modifications, or cancellations. Nasdaq is the most active US equity exchange by volume and represented 13.03% of the average daily volume (ADV) as of January 2025.

With its L3 granularity, Nasdaq TotalView-ITCH captures information beyond the L1, top-of-book data available through SIP feeds and enables more accurate modeling of book imbalances, trade directionality, quote lifetimes, and more. This includes explicit trade aggressor side, odd lots, auction imbalance data, and the Net Order Imbalance Indicator (NOII) for the Nasdaq Opening and Closing Crosses and Nasdaq IPO/Halt Cross—the best predictor of Nasdaq opening and closing prices available. Other key advantages of Nasdaq TotalView-ITCH over SIP data include faster real-time dissemination and precise exchange-side timestamping directly from Nasdaq.

Real-time Nasdaq TotalView-ITCH data is included with a Plus or Unlimited subscription through our Databento US Equities service. Historical data is available for usage-based rates or with any subscription. Visit our pricing page for more details or to upgrade your plan.

Breadth of coverage: 20,329 products

Asset class(es): Equities

Origin: Directly captured at Equinix NY4 (Secaucus, NJ) with an FPGA-based network card and hardware timestamping. Synchronized to UTC with PTP.

Supported data encodings: DBN, CSV, JSON Learn more

Supported market data schemas: MBO, MBP-1, MBP-10, BBO-1s, BBO-1m, TBBO, Trades, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Statistics, Status, Imbalance Learn more

Resolution: Immediate publication, nanosecond-resolution timestamps

Context

This dataset contains historical data of stocks listed on IHSG with time ranges per minutes, hourly, and daily. The source of the dataset is taken from Yahoo Finance's public data and the IDX website which is listed in the metadata tab. This dataset was created with the intention of academic research purposes and not to be commercialized. If you have questions about the dataset, please ask in the discussion tab. Code snippet: https://github.com/muamkh/IHSGstockscraper

Content

Stock minutes data is taken from 1 November 2021 until 6 January 2023. Stock hourly data is taken from 16 April 2020 until 6 January 2023. Stock daily data is taken from 16 April 2001 until 6 January 2023. All of the data is using CSV format. Stock data isnt adjusted with dividend, stock split, and other corporate action.

Stocklist Structure

• Code = Stock code
• Name = Company name
• ListingDate = Listing date of stock on Indonesia Stock Exchange
• Shares = Amount of shares
• ListingBoard = Board category (Main Board, Development Board or Acceleration). More info: https://www.idx.co.id/en-us/products/stocks/
• Sector = Sector Category based on IDX-IC. More info: https://www.idx.co.id/en-us/products/stocks/
• LastPrice = Last stock price
• MarketCap = Market Capitalization.
• MinutesFirstAdded = Date the data first retrieved in minute range
• MinutesLastAdded = Date the data last retrieved in minute range
• HourlyFirstAdded = Date the data first retrieved in hourly range
• HourlyLastAdded = Date the data last retrieved in hourly range
• DailyFirstAdded = Date the data first retrieved in daily range
• DailyLastAdded = Date the data last retrieved in daily range

Struktur Data Saham

• timestamp = Date and time of stock transaction
• open = opening price
• low = lowest price in the timespan
• high = highest price in the timespan
• close = closing price
• volume = Total volume traded in the timespan

The dataset contains historical technical data of Dhaka Stock Exchange (DSE). The data was collected from different sources found in the internet where the data was publicly available. The data available here are used for information and research purposes and though to the best of our knowledge, it does not contain any mistakes, there might still be some mistakes. It is not encourages to use this dataset for portfolio management purposes and use this dataset out of your own interest. The contributors do not hold any liability if it is used for any purposes.

Graph and download economic data for CBOE Volatility Index: VIX (VIXCLS) from 1990-01-02 to 2025-07-10 about VIX, volatility, stock market, and USA.

This dataset provides comprehensive daily stock and leveraged ETF data for NVDA (NVIDIA Corporation) and NVDL (Direxion Daily Semiconductor Bull 3X Shares) from 2020 to 2024. It includes key market indicators such as open, close, high, low, and volume data for both assets, allowing users to analyze trends, volatility, and market performance over time.

The dataset is suitable for financial analysis, algorithmic trading models, and machine learning applications focused on stock and ETF performance. Whether you're exploring price movements, developing prediction models, or studying market patterns, this dataset offers valuable insights into NVDA and NVDL.

Key features:

• Date range: 2020–2024
• Assets covered: NVDA (NVIDIA Corporation), NVDL (Leveraged ETF)
• Data points: Open, close, high, low, volume
• Ideal for: Financial analysis, time series forecasting, market trend exploration

Feel free to download and explore this dataset for your financial analysis and research needs. Let me know if you'd like further customization!

S&P 500 index data including level, dividend, earnings and P/E ratio on a monthly basis since 1870. The S&P 500 (Standard and Poor's 500) is a free-float, capitalization-weighted index of the top ...

List of companies in the NYSE, and other exchanges.

Data and documentation are available on NASDAQ's official webpage. Data is updated regularly on the FTP site.

The file used in this repository: ...

Browse S&P 500 Index (SPX) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

Consolidated last sale, exchange BBO and national BBO across all US equity options exchanges. Includes single name stock options (e.g. TSLA), options on ETFs (e.g. SPY, QQQ), index options (e.g. VIX), and some indices (e.g. SPIKE and VSPKE). This dataset is based on the newer, binary OPRA feed after the migration to SIAC's OPRA Pillar SIP in 2021. OPRA is notable for the size of its data and we recommend users to anticipate several TBs of data per day for the full dataset in its highest granularity (MBP-1).

Origin: Options Price Reporting Authority

Supported data encodings: DBN, JSON, CSV Learn more

Supported market data schemas: MBP-1, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, TBBO, Trades, Statistics, Definition Learn more

Resolution: Immediate publication, nanosecond-resolution timestamps