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.

Graph and download economic data for Dow Jones Industrial Average (DJIA) from 2015-07-13 to 2025-07-11 about stock market, average, industry, and USA.

Overview

This dataset contains historical daily prices for all tickers currently trading on NASDAQ. The up to date list is available from nasdaqtrader.com. The historic data is retrieved from Yahoo finance via yfinance python package.

It contains prices for up to 01 of April 2020. If you need more up to date data, just fork and re-run data collection script also available from Kaggle.

Data Structure

The date for every symbol is saved in CSV format with common fields:

• Date - specifies trading date
• Open - opening price
• High - maximum price during the day
• Low - minimum price during the day
• Close - close price adjusted for splits
• Adj Close - adjusted close price adjusted for both dividends and splits.
• Volume - the number of shares that changed hands during a given day

All that ticker data is then stored in either ETFs or stocks folder, depending on a type. Moreover, each filename is the corresponding ticker symbol. At last, symbols_valid_meta.csv contains some additional metadata for each ticker such as full name.

The main stock market index of United States, the US500, fell to 6226 points on July 14, 2025, losing 0.54% from the previous session. Over the past month, the index has climbed 3.20% and is up 10.56% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

Please see code repository. https://github.com/nlandolfi/acc2022treelinearcascades_stocks

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.

Context

Stock time series are a favourite among data scientists because they are easily understood and widely available - in this extensive data set you will find long-time time-series with open/close/high/min/adjusted features, as well as data regarding stock splits, trading volume and dividends.

Content

This data set includes Dow Jones member stock prices (status 01.0.1.2021) with all their historic stock performances from 01.01.2020 to 31.12.2020.

• 30 Dow Jones stocks
• 21 years of data (depending on company age)
• 1 entry per day
• 150503 data points

Please also check the corresponding Jupyter Notebook to get some basic ideas how to use this data set: https://www.kaggle.com/deeplytics/dow-jones-historic-stock-data-2000-2020

Stock Names

In the data set, all companies use their stock ticker names. If you are unfamiliar with them, please check this overview: https://www.cnbc.com/dow-30/

Inspiration

Today's free APIs and coding libraries make it relatively easy for the average user to get an understanding of stock price movements. More advanced users may even be able to find patterns, that can be incorporated into investment decisions.

Acknowledgements

Photo by Dmitry Demidko on Unsplash: https://unsplash.com/photos/eBWzFKahEaU?utm_source=unsplash&utm_medium=referral&utm_content=creditShareLink

Japan's main stock market index, the JP225, fell to 39432 points on July 14, 2025, losing 0.35% from the previous session. Over the past month, the index has climbed 2.93%, though it remains 4.47% lower than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Japan. Japan Stock Market Index (JP225) - values, historical data, forecasts and news - updated on July of 2025.

The main stock market index of United States, the US500, fell to 6238 points on July 4, 2025, losing 0.65% from the previous session. Over the past month, the index has climbed 5.04% and is up 12.06% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

Graph and download economic data for Dow-Jones Industrial Stock Price Index for United States (M1109BUSM293NNBR) from Dec 1914 to Dec 1968 about stock market, industry, price index, indexes, price, and USA.

Dow-Jones Industrial Stock Index: 54 years of historical data from 1914 to 1968.

The main stock market index of United States, the US500, fell to 6260 points on July 11, 2025, losing 0.33% from the previous session. Over the past month, the index has climbed 3.55% and is up 11.48% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.

Experimental studies in the area of Psychology and Behavioral Economics have suggested that people change their search pattern in response to positive and negative events. Using Internet search data provided by Google, we investigated the relationship between stock-specific events and related Google searches. We studied daily data from 13 stocks from the Dow-Jones and NASDAQ100 indices, over a period of 4 trading years. Focusing on periods in which stocks were extensively searched (Intensive Search Periods), we found a correlation between the magnitude of stock returns at the beginning of the period and the volume, peak, and duration of search generated during the period. This relation between magnitudes of stock returns and subsequent searches was considerably magnified in periods following negative stock returns. Yet, we did not find that intensive search periods following losses were associated with more Google searches than periods following gains. Thus, rather than increasing search, losses improved the fit between people’s search behavior and the extent of real-world events triggering the search. The findings demonstrate the robustness of the attentional effect of losses.

New York Stock Exchange: Index: Dow Jones US Automobiles & Parts Index data was reported at 1,079.390 NA in Apr 2025. This records an increase from the previous number of 1,008.630 NA for Mar 2025. New York Stock Exchange: Index: Dow Jones US Automobiles & Parts Index data is updated monthly, averaging 998.810 NA from Mar 2024 (Median) to Apr 2025, with 14 observations. The data reached an all-time high of 1,480.710 NA in Dec 2024 and a record low of 786.250 NA in May 2024. New York Stock Exchange: Index: Dow Jones US Automobiles & Parts Index data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s United States – Table US.EDI.SE: New York Stock Exchange: Dow Jones: Monthly.

Dow30 Stock Prediction Dataset

  Overview

Welcome to the Dow30 Stock Prediction dataset! This dataset is designed to assist in predicting stock returns for companies in the Dow Jones Industrial Average (Dow30). It includes essential information about each company, such as news from the last two weeks, basic financial data, and stock prices over the same period.

  Dataset Structure

The dataset consists of the following columns:

prompt: Information about the company… See the full description on the dataset page: https://huggingface.co/datasets/descartes100/Dow30_stock_prediction.

The dataset consists of daily data from US Dow Jones for 501 large companies, over the time span 2010-2016, while monthly publicly available indexes are also used.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

The Dow Jones U.S. Completion Total Stock Market Index

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

New York Stock Exchange: Index: Dow Jones US Oil & Gas Index data was reported at 675.620 NA in Apr 2025. This records a decrease from the previous number of 780.190 NA for Mar 2025. New York Stock Exchange: Index: Dow Jones US Oil & Gas Index data is updated monthly, averaging 594.840 NA from Aug 2013 (Median) to Apr 2025, with 141 observations. The data reached an all-time high of 846.020 NA in Jun 2014 and a record low of 239.560 NA in Mar 2020. New York Stock Exchange: Index: Dow Jones US Oil & Gas Index data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s United States – Table US.EDI.SE: New York Stock Exchange: Dow Jones: Monthly.

United States New York Stock Exchange: Index: Dow Jones US Diversified REITs Index data was reported at 53.680 NA in Apr 2025. This records a decrease from the previous number of 54.260 NA for Mar 2025. United States New York Stock Exchange: Index: Dow Jones US Diversified REITs Index data is updated monthly, averaging 77.130 NA from Jan 2012 (Median) to Apr 2025, with 160 observations. The data reached an all-time high of 105.270 NA in Apr 2013 and a record low of 45.550 NA in Oct 2023. United States New York Stock Exchange: Index: Dow Jones US Diversified REITs Index data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s United States – Table US.EDI.SE: New York Stock Exchange: Dow Jones: Monthly.