These daily weather records were compiled from a subset of stations in the Global Historical Climatological Network (GHCN)-Daily dataset. A weather record is considered broken if the value exceeds the maximum (or minimum) value recorded for an eligible station. A weather record is considered tied if the value is the same as the maximum (or minimum) value recorded for an eligible station. Daily weather parameters include Highest Min/Max Temperature, Lowest Min/Max Temperature, Highest Precipitation, Highest Snowfall and Highest Snow Depth. All stations meet defined eligibility criteria. For this application, a station is defined as the complete daily weather records at a particular location, having a unique identifier in the GHCN-Daily dataset. For a station to be considered for any weather parameter, it must have a minimum of 30 years of data with more than 182 days complete in each year. This is effectively a 30-year record of service requirement, but allows for inclusion of some stations which routinely shut down during certain seasons. Small station moves, such as a move from one property to an adjacent property, may occur within a station history. However, larger moves, such as a station moving from downtown to the city airport, generally result in the commissioning of a new station identifier. This tool treats each of these histories as a different station. In this way, it does not thread the separate histories into one record for a city. Records Timescales are characterized in three ways. In order of increasing noteworthiness, they are Daily Records, Monthly Records and All Time Records. For a given station, Daily Records refers to the specific calendar day: (e.g., the value recorded on March 7th compared to every other March 7th). Monthly Records exceed all values observed within the specified month (e.g., the value recorded on March 7th compared to all values recorded in every March). All-Time Records exceed the record of all observations, for any date, in a station's period of record. The Date Range and Location features are used to define the time and location ranges which are of interest to the user. For example, selecting a date range of March 1, 2012 through March 15, 2012 will return a list of records broken or tied on those 15 days. The Location Category and Country menus allow the user to define the geographic extent of the records of interest. For example, selecting Oklahoma will narrow the returned list of records to those that occurred in the state of Oklahoma, USA. The number of records broken for several recent periods is summarized in the table and updated daily. Due to late-arriving data, the number of recent records is likely underrepresented in all categories, but the ratio of records (warm to cold, for example) should be a fairly strong estimate of a final outcome. There are many more precipitation stations than temperature stations, so the raw number of precipitation records will likely exceed the number of temperature records in most climatic situations.

Dataset historical price data for XAU/USD (gold vs USD) from 2004 to Feb 2025, captured across multiple timeframes including 5-minute, 15-minute, 30-minute, 1-hour, 4-hour, daily, weekly, and monthly intervals. Dataset includes Open, High, Low, Close prices, and Volume data.

Download Historical E Mini S&P Futures Data. CQG daily, 1 minute, tick, and level 1 data from 1899.

Provides an aggregate of data for the Office of the Actuary and the Office of Research, Evaluation and Statistics.

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.

A set of three estimates of land-cover types and annual transformations of land use are provided on a global 0.5 x0.5 degree lat/lon grid at annual time steps. The longest of the three estimates spans 1770-2010. The dataset presented here takes into account land-cover change due to four major land-use/management activities: (1) cropland expansion and abandonment, (2) pastureland expansion and abandonment, (3) urbanization, and (4) secondary forest regrowth due to wood harvest. Due to uncertainties associated with estimating historical agricultural (crops and pastures) land use, the study uses three widely accepted global reconstruction of cropland and pastureland in combination with common wood harvest and urban land data set to provide three distinct estimates of historical land-cover change and underlying land-use conversions. Hence, these distinct historical reconstructions offer a wide range of plausible regional estimates of uncertainty and extent to which different ecosystem have undergone changes. The three estimates use a consistent methodology, and start with a common land-cover map during pre-industrial conditions (year 1765), taking different courses as determined by the land-use/management datasets (cropland, pastureland, urbanization and wood harvest) to attain forest area distributions close to satellite estimates of forests for contemporary period. The satellite based estimates of forest area are based on MODIS sensor. All data uses the WGS84 spatial coordinate system for mapping.

You can check the fields description in the documentation: current Full database: https://docs.dataforseo.com/v3/databases/google/full/?bash; Historical Full database: https://docs.dataforseo.com/v3/databases/google/history/full/?bash.

Full Google Database is a combination of the Advanced Google SERP Database and Google Keyword Database.

Google SERP Database offers millions of SERPs collected in 67 regions with most of Google’s advanced SERP features, including featured snippets, knowledge graphs, people also ask sections, top stories, and more.

Google Keyword Database encompasses billions of search terms enriched with related Google Ads data: search volume trends, CPC, competition, and more.

This database is available in JSON format only.

You don’t have to download fresh data dumps in JSON – we can deliver data straight to your storage or database. We send terrabytes of data to dozens of customers every month using Amazon S3, Google Cloud Storage, Microsoft Azure Blob, Eleasticsearch, and Google Big Query. Let us know if you’d like to get your data to any other storage or database.

Historical National Boundaries displays global national boundaries for the following dates in history: 1800, 1914, 1918, 1939, 1945, 1970, 1990, 2000. Boundary changes associated with World War I (1914 - 1918) and World War II (1939 - 1945) can be viewed by turning off all other layers and toggling between the two. Data for each layer comes from a variety of sources, including historical atlases and the Library of Congress website - https://www.loc.gov/maps/. Suggested CitationKropelnicki, Jeffrey; Johnson, Grace; Kne, Len; Lindberg, Mark. (2022). Historical National Boundaries. Retrieved from the Data Repository for the University of Minnesota, https://doi.org/10.13020/146x-1412.

To preserve NEFSC historical data, images of biological and oceanographic data sheets (1948-1975) were scanned to digital format and can be queried through a portal on the NEFSC website. Images may include: cruise instructions, cruise tracks, original trawl logs, length frequency data sheets, cruise notes, tagging information and fisherman reports.

Data for A History of Open Temperature and Rainfall with Uncertainty in New Zealand (HOTRUNZ): an open access 1 km resolution monthly 1910-2019 time-series of interpolated temperature and rainfall grids with associated uncertainty. The files use the open GeoTIFF geospatial data standard, that are compressed using the open 7z compression file format. There is data for both: nni: the variable estimate from natural neighbour interpolation unc: the uncertainty of the variable estimate for four weather variables: rain: total rainfall (mm) tavg: mean air temperature (°C) tmin: mean daily minimum air temperature (°C) tmax: mean daily maximum air temperature (°C) and these variables help form the file names alongside the year and month. So for example, nni-rain-1910-01.tif contains the natural neighbour interpolated values for total rainfall in January 1910, and unc-tavg-1979-05.tif contains the uncertainty values for mean air temperature in May 1979. For storage efficiency when archiving the data, all data value were multiplied by 10 so that they could be stored as 16 bit integer files. Therefore, all the data needs to be divided by 10 to restore the actual data values before the data is used for any analysis. For users outside of New Zealand who are struggling to download the large data files from here, these data files can also be downloaded from Zenodo at https://zenodo.org/record/5703749. There are also notes on how to source the input data used to create HOTRUNZ.

Unemployment Rate in the United States decreased to 4.10 percent in June from 4.20 percent in May of 2025. This dataset provides the latest reported value for - United States Unemployment Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

The Global Historical Climatology Network - Daily (GHCN-Daily/GHCNd) dataset integrates daily climate observations from approximately 30 different data sources. Version 3 was released in September 2012 with the addition of data from two additional station networks. Changes to the processing system associated with the version 3 release also allowed for updates to occur 7 days a week rather than only on most weekdays. Version 3 contains station-based measurements from well over 90,000 land-based stations worldwide, about two thirds of which are for precipitation measurement only. Other meteorological elements include, but are not limited to, daily maximum and minimum temperature, temperature at the time of observation, snowfall and snow depth. Over 25,000 stations are regularly updated with observations from within roughly the last month. The dataset is also routinely reconstructed (usually every week) from its roughly 30 data sources to ensure that GHCNd is generally in sync with its growing list of constituent sources. During this process, quality assurance checks are applied to the full dataset. Where possible, GHCNd station data are also updated daily from a variety of data streams. Station values for each daily update also undergo a suite of quality checks.

Interactive chart of the S&P 500 stock market index since 1927. Historical data is inflation-adjusted using the headline CPI and each data point represents the month-end closing value. The current month is updated on an hourly basis with today's latest value.

Retail Sales in the United States decreased 0.90 percent in May of 2025 over the previous month. This dataset provides - U.S. December Retail Sales Increased More Than Forecast - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Our extensive historical database captures every significant market movement, from the earliest Bitcoin trades through today's crypto ecosystem, across 350+ global exchanges.

This rich historical dataset serves multiple critical functions: from enabling sophisticated strategy backtesting and long-term trend analysis to supporting academic research and trading pattern identification. Whether analyzing market volatility, studying price correlations, or conducting deep market research, our historical data provides the reliable foundation needed for meaningful cryptocurrency market analysis.

Why work with us?

Market Coverage & Data Types: - Real-time and historical data since 2010 (for chosen assets) - Full order book depth (L2/L3) - Tick-by-tick data - OHLCV across multiple timeframes - Market indexes (VWAP, PRIMKT) - Exchange rates with fiat pairs - Spot, futures, options, and perpetual contracts - Coverage of 90%+ global trading volume - Full Cryptocurrency Investor Data

Technical Excellence: - 99,9% uptime guarantee - Multiple delivery methods: REST, WebSocket, FIX, S3 - Standardized data format across exchanges - Ultra-low latency data streaming - Detailed documentation - Custom integration assistance

CoinAPI serves hundreds of institutions worldwide, from trading firms and hedge funds to research organizations and technology providers. Our commitment to data quality and technical excellence makes us the trusted choice for cryptocurrency market data needs.

The Gross Domestic Product (GDP) in the United States was worth 29184.89 billion US dollars in 2024, according to official data from the World Bank. The GDP value of the United States represents 27.49 percent of the world economy. This dataset provides - United States GDP - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Historical data on the modern Olympics from Athens 1896 to Rio 2016. The data was scraped from www.sports-reference.com in May 2018. The file athlete_events.csv contains 271116 rows and 15 columns. Each row corresponds to an individual athlete competing in an individual Olympic event (athlete-events). The columns are:1. ID - Row numbers2. Name - Athlete's name3. Sex - M or F4. Age - Integer5. Height - In centimeters6. Weight - In kilograms7. Team - Team name8. NOC - National Olympic Committee 3-letter code9. Games - Year and season10. Year - Integer11. Season - Summer or Winter12. City - Host city13. Sport - Sport14. Event - Event15. Medal - Gold, Silver, Bronze, or NAFor more information:About the sports-reference Olympic database: http://olympstats.com/2016/08/21/the-olymadmen-and-olympstats-and-sports-reference/About how I scraped the data: https://rgriff23.github.io/2018/05/27/olympic-history-1-web-scraping.htmlAbout how I wrangled the data: https://rgriff23.github.io/2018/05/28/olympic-history-2-data-wrangling-1.htmlhttps://rgriff23.github.io/2018/05/28/olympic-history-3-data-wrangling-2.htmlMy GitHub repo for this project, including analyses using this data:https://github.com/rgriff23/Olympic_history

Historical option EOD data in 2021, dataset files in CSV format.

Beginning in the mid-1900s , naturalist Daniel Smiley and his associates and successors at the Daniel Smiley Research Center documented extensive natural history observations of the flora and fauna of the Shawangunk Ridge on over 14,000 3x5” index cards. Observations are highly detailed and often include narrative descriptions as well as basic observational information. The duration, extent and specificity of this dataset provide a wealth of information to support and inform biodiversity research, environmental management and ecological sciences.

Inflation Rate in the United States increased to 2.40 percent in May from 2.30 percent in April of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.