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, rose to 6464 points on September 1, 2025, gaining 0.06% from the previous session. Over the past month, the index has climbed 2.13% and is up 16.92% 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 September of 2025.

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.

Prices for United States Stock Market Index (US500) including live quotes, historical charts and news. United States Stock Market Index (US500) was last updated by Trading Economics this August 31 of 2025.

Germany's main stock market index, the DE40, rose to 24002 points on September 1, 2025, gaining 0.42% from the previous session. Over the past month, the index has climbed 1.03% and is up 26.79% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Germany. Germany Stock Market Index (DE40) - values, historical data, forecasts and news - updated on September of 2025.

This dataset contains 20+ years of all items in the American art category sold on auction by Christie’s, Sotheby’s, Bonhams and Phillips from 2000 to date.

Sweetener Market Data (SMD) report - beet and cane processors and cane refiners in the U.S. are required by the FAIR Act of 1996, as amended, to report data on physical quantities delivered by use for "Multiple and All Other Food Uses" on a monthly basis. Quantities are reported by region. Regions include: "New England", "Mid Atlantic", "North Central", "South", "West" and "Puerto Rico".

France's main stock market index, the FR40, fell to 7655 points on September 2, 2025, losing 0.69% from the previous session. Over the past month, the index has climbed 0.30% and is up 1.05% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from France. France Stock Market Index (FR40) - values, historical data, forecasts and news - updated on September of 2025.

Sweetener Market Data (SMD) report - beet and cane processors and cane refiners in the U.S. are required by the FAIR Act of 1996, as amended, to report data on physical quantities delivered by use in the West region on a monthly basis. Uses include "Bakery, Cereal and Related Products"; "Confectionery and Related Products"; "Ice Cream and Related Products"; "Beverages"; "Canned, Bottled and Frozen Foods"; "Multiple and All Other Food Uses", "Non-Food Uses", "Hotels, Restaurants and Institutions"; "Wholesale Grocers, Jobbers and Dealers", "Retail Grocers and Chain Stores", "Deliveries to Government Agencies", and "All Other Deliveries".

Sweetener Market Data (SMD) report - beet and cane processors and cane refiners in the U.S. are required by the FAIR Act of 1996, as amended, to report data on physical quantities delivered by use in the North Central region on a monthly basis. Uses include "Bakery, Cereal and Related Products"; "Confectionery and Related Products"; "Ice Cream and Related Products"; "Beverages"; "Canned, Bottled and Frozen Foods"; "Multiple and All Other Food Uses", "Non-Food Uses", "Hotels, Restaurants and Institutions"; "Wholesale Grocers, Jobbers and Dealers", "Retail Grocers and Chain Stores", "Deliveries to Government Agencies", and "All Other Deliveries".

Sweetener Market Data (SMD) report - beet and cane processors and cane refiners in the U.S. are required by the FAIR Act of 1996, as amended, to report data on physical quantities delivered by use for "Government Agencies" on a monthly basis. Quantities are reported by region. Regions include: "New England", "Mid Atlantic", "North Central", "South", "West" and "Puerto Rico".This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Web Page For complete information, please visit https://data.gov.

Context

Stock market data can be interesting to analyze and as a further incentive, strong predictive models can have large financial payoff. The amount of financial data on the web is seemingly endless. A large and well structured dataset on a wide array of companies can be hard to come by. Here I provide a dataset with historical stock prices (last 5 years) for all companies currently found on the S&P 500 index.

The script I used to acquire all of these .csv files can be found in this GitHub repository In the future if you wish for a more up to date dataset, this can be used to acquire new versions of the .csv files.

Content

The data is presented in a couple of formats to suit different individual's needs or computational limitations. I have included files containing 5 years of stock data (in the all_stocks_5yr.csv and corresponding folder) and a smaller version of the dataset (all_stocks_1yr.csv) with only the past year's stock data for those wishing to use something more manageable in size.

The folder individual_stocks_5yr contains files of data for individual stocks, labelled by their stock ticker name. The all_stocks_5yr.csv and all_stocks_1yr.csv contain this same data, presented in merged .csv files. Depending on the intended use (graphing, modelling etc.) the user may prefer one of these given formats.

All the files have the following columns: Date - in format: yy-mm-dd Open - price of the stock at market open (this is NYSE data so all in USD) High - Highest price reached in the day Low Close - Lowest price reached in the day Volume - Number of shares traded Name - the stock's ticker name

Acknowledgements

I scraped this data from Google finance using the python library 'pandas_datareader'. Special thanks to Kaggle, Github and The Market.

Inspiration

This dataset lends itself to a some very interesting visualizations. One can look at simple things like how prices change over time, graph an compare multiple stocks at once, or generate and graph new metrics from the data provided. From these data informative stock stats such as volatility and moving averages can be easily calculated. The million dollar question is: can you develop a model that can beat the market and allow you to make statistically informed trades!

The Dow Jones Industrial Average (DJIA) index dropped around ***** points in the four weeks from February 12 to March 11, 2020, but has since recovered and peaked at ********* points as of November 24, 2024. In February 2020 - just prior to the global coronavirus (COVID-19) pandemic, the DJIA index stood at a little over ****** points. U.S. markets suffer as virus spreads The COVID-19 pandemic triggered a turbulent period for stock markets – the S&P 500 and Nasdaq Composite also recorded dramatic drops. At the start of February, some analysts remained optimistic that the outbreak would ease. However, the increased spread of the virus started to hit investor confidence, prompting a record plunge in the stock markets. The Dow dropped by more than ***** points in the week from February 21 to February 28, which was a fall of **** percent – its worst percentage loss in a week since October 2008. Stock markets offer valuable economic insights The Dow Jones Industrial Average is a stock market index that monitors the share prices of the 30 largest companies in the United States. By studying the performance of the listed companies, analysts can gauge the strength of the domestic economy. If investors are confident in a company’s future, they will buy its stocks. The uncertainty of the coronavirus sparked fears of an economic crisis, and many traders decided that investment during the pandemic was too risky.

• Data from Dec 1989 to Dec 2020.
• Includes Income Statement, Balance Sheet, and Cashflow statement.
• Adjusted for restatements.
• Includes valuation metrics such as enterprise valuation and market capitalization.
• Over 30 ratios such as p/e ratio, EBITDA/sales, gross margin etc..
• Standardized categories for comparison between companies.

Israel's main stock market index, the TA-125, fell to 3098 points on September 1, 2025, losing 0.54% from the previous session. Over the past month, the index has climbed 0.59% and is up 48.68% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Israel. Israel Stock Market (TA-125) - values, historical data, forecasts and news - updated on September 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.

Smart Insider’s Global Share Buyback Database offers invaluable insights to investors on stock market data. We provide detailed, up-to-date share buyback data covering over 55,000 companies globally and over 8,000+ in Europe & UK, that’s every company that reports Buybacks through regulatory processes.

Our Share buyback data includes detailed information on all major buyback transactions including source announcements and derived analysis fields. Our platform adds a visual representation of the data, allowing investors to quickly identify patterns and make decisions based on their findings.

Get detailed share buyback insights with Smart Insider and stay ahead of the curve with accurate, historical buyback insight that helps you make better investment decisions.

We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as CSV, XML or XLSX via SFTP, API or Snowflake.

Sample dataset for Desktop Service has been provided with limited fields. Upon request, we can provide a detailed Quant sample.

Tags: Equity Market Data, Stock Market Data, Corporate Actions Data, Corporate Buyback Data, Company Financial Data, Insider Trading Data

Sweetener Market Data (SMD) report - beet and cane processors and cane refiners in the U.S. are required by the FAIR Act of 1996, as amended, to report data on physical quantities delivered by use in Puerto Rico on a monthly basis. Uses include "Bakery, Cereal and Related Products"; "Confectionery and Related Products"; "Ice Cream and Related Products"; "Beverages"; "Canned, Bottled and Frozen Foods"; "Multiple and All Other Food Uses", "Non-Food Uses", "Hotels, Restaurants and Institutions"; "Wholesale Grocers, Jobbers and Dealers", "Retail Grocers and Chain Stores", "Deliveries to Government Agencies", and "All Other Deliveries".This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Web Page For complete information, please visit https://data.gov.

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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.