Current and historical exchanges rates for 120+ currencies relative to USD provided in bulk and via API. Earliest historical data is 2011-09-31.

Data

Every hour, Currency Bot queries a currency conversion provider (currency.me.uk, formerly the Google Calculator API, and potentially a few others in the near future) collecting all the conversion rates for all currencies one-by-one, then saving them into a formatted API JSON file and pushing it to GitHub for everyone to use as an open-source API.

You can use this data to perform JavaScript currency conversion on the client-side (eg. for a web-app or online store - try money.js) or for back-end processing (eg. databases, analytics, whatever).

It's mirrored on http://openexchangerates.org with friendly Access-Control HTTP headers, so that you can load it in via AJAX with a cross-domain request without worrying about browser security restrictions.

As with all exchange rate data, accuracy can never be guaranteed when you're not paying through the teeth for the service - and when money changes currencies, everyone takes a cut (not to be trusted!) - so it's a good idea to inform people that these are for informational purposes only, something like "Converted prices/exchange rates are for informational purposes only." Feel free to say that rates come form the Open Source Exchange Rates API.

Openness: Not Open

Update: 2012-07-16. Data is not open (non-commercial restrictions). To quote from the the license page:

The Data available through the Service and the Project is released under a non-commercial license. This means that you may not resell or directly profit from, or cause any entity to profit from, direct sale or provision of the Data.

You may use the Data to build services that are informed by it inside commercial applications (for example, a currency conversion widget for shopping cart software, or to provide points of reference for statistical diagrams and graphs).

In a nutshell: You are not permitted to sell or profit directly from the Data, or by providing access to the Data; but you are permitted to use it inside commercial applications, provided that the Data itself is not the product being sold or direct cause of any profit.

Note also that the data does not originate from this project but is sourced from elsewhere. As such it's not clear what exactly its openness is. Again to quote from the license page:

Exchange rates (the "Data") are collected regularly from various free providers and sources (see list, below) in accordance with their respective robots.txt directives (if any) and Terms and Conditions. No laws or legal policies are broken in order to collect the Data. Having obeyed Terms and Conditions and related directives, the Project can and will not be held liable for legal claim or damages caused by collection, or usage by any party, of this Data.

ECB reference exchange rate, Canadian dollar, US dollar, Mexican peso, UK pound sterling / Euro

Gain exclusive access to specialist Foreign Exchange (FX) data, and the tools to manage trading analysis, risk and operations with LSEG's FX Pricing Data.

Daily bulletin time series available since 2/1/2002, for the Euro, and since 28/11/1984, for the other currencies. For the American Dollar, this data set shows administered rates until March, 1990 and free rates from then on (Resolution 1690/1990). Administered rates are those set by the Central Bank of Brazil; from March, 1992, this rate started being called Ptax rate (close). Until 30/6/2011, this rate was calculated as the average rate, weighed by volume, of all interbank operations traded on that day. Starting on 1/7/2011 (Circular 3506/2010), the Ptax rate calculation corresponds to the arithmetic average of four daily quotes provided by Central Bank of Brazil’s foreign exchange dealers; the quotes must reflect market conditions at that time. Parities of the other currencies against the American Dollar (USD) are obtained from information agencies. Currencies rates against the Brazilian currency are calculated dividing the Brazilian currency rate against the American Dollar by the parities against the American Dollar for type A currencies, and multiplying the Brazilian currency rate against the American Dollar by the parities against the American Dollar for type B currencies. Available currencies: Danish Krone (DKK) Type A Norwegian Krone (NOK) Type A Swedish Krona (SEK) Type A American Dollar (USD) Type A Australian Dollar (AUD) Type B Canadian Dollar (CAD) Type A Euro (EUR) Type B Swiss Franc (CHF) Type A Japanese Yen (JPY) Type A British Pound (GBP) Type B Unit of measure: Type A currencies: Parity (American Dollar): quantity in the currency per one unit of American Dollar (USD); Rates (Brazilian currency): quantity in the Brazilian currency per one unit of the currency Type B currencies: Parity (American Dollar): quantity in American Dollars (USD) per one unit of the currency; Rates (Brazilian currency): quantity in the Brazilian currency per one unit of the currency Example of how to calculate type A currencies rates in the Brazilian currency, considering the Real (BRL) as the domestic currency and the Canadian Dollar (CAD) as the foreign currency: CADBRL bid rate = USDBRL bid rate ÷ USDCAD offer parity CADBRL offer rate = USDBRL offer rate ÷ USDCAD bid parity Example of how to calculate type B currencies rates in the Brazilian currency, considering the Real (BRL) as the domestic currency and the Euro (EUR) as the foreign currency: EURBRL bid rate = EURUSD bid parity × USDBRL bid rate EURBRL offer rate = EURUSD offer parity × USDBRL offer rate Source: Refinitiv, except for USDBRL The Central Bank assumes no responsibility whatsoever for non-simultaneity or any lack of information, as well as for possible errors in currency parities or any other errors, except the parity of the United States dollar in relation to the Real. The institution also assumes no responsibilty for delays or the unavailability of telecommunications services, interruptions, failures or imprecisions in the providing of the services or information. The Central Bank likewise assumes no responsibility for any losses or damages consequent upon such interruptions, delays, failings or imperfections, as well as for the inadequate use of the information contained in the transaction. af829095-9d8c-4c1d-a77f-48e4d51f7a71 exchange-rates-daily-bulletins

Context

I have generated this set of auxilary tables to complement the dataset of Kickstarter projects with the focus on videogames.

Content

Currently the set contains three tables:

SteamSpy table contains aggregate information on released games tracked by SteamSpy

KSreleased table links the Steam appid's with Kickstarter project IDs for those KS games, that after a successful campaign were finished and released on Steam

Currencies table shows historical currency exchange rates to USD($) for each week since the earliest campaign deadline among those in KSreleased

Acknowledgements

SteamSpy table was created using the site's API and I would like to take this opportunity to praise the site's creator Sergey Galyonkin

KSreleased table was generated by crawling Kickstarter "Play now" pages

Currencies table was generated using Fixer.io API

If you would like to know the details/see the code that I wrote to generate the data, I uploaded it as the "DEMO: generate data" kernel. It won't work online (otherwise I wouldn't have the need to create the dataset in the first place), but you can download the notebook and run it locally or just check my poor coding style :)

Inspiration

I intend to finalize my analysis on KS games that were released on Steam and publish it here, but of course I would like you to find more uses for this data beyond what I would have thought of. And again, I don't think this dataset is useful on its own, so please don't forget to connect to the KS projects dataset by Kemical

This table contains 27 series, with data starting from 1981 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada) Type of currency (27 items: Australian dollar, monthly average; Brazilian real, monthly average; Chinese renminbi, monthly average; European euro, monthly average; ...).

CoinAPI's crypto OHLCV and trade data give you the complete picture of market activity across more than 350 exchanges worldwide. Our candlestick data covers everything from 1-second intervals for scalping to monthly timeframes for trend analysis, ensuring you have the right level of detail for your trading approach.

Each candlestick provides the essential price information traders rely on - open, high, low, and close prices - along with corresponding volume data that shows the market strength behind each move. This combination of price action and trading volume creates the foundation for effective technical analysis and trading decisions.

Getting this data is straightforward - use our WebSocket streams for real-time market monitoring when every second counts, or access historical candlesticks through our REST API when you're conducting deeper market research or backtesting strategies. We maintain comprehensive historical records, giving you the ability to analyze patterns across different market cycles.

Why work with us?

Market Coverage & Data Types: - Full Cryptocurrency Data - 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

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

Whether you're building algorithmic trading systems, conducting research, or creating visualization tools, our real-time and historical candlesticks from exchanges worldwide provide the reliable market data you need

Extensive and dependable pricing information spanning the entire range of financial markets. Encompassing worldwide coverage from stock exchanges, trading platforms, indicative contributed prices, assessed valuations, expert third-party sources, and our enhanced data offerings. User-friendly request-response, bulk access, and tailored desktop interfaces to meet nearly any organizational or application data need. Worldwide, real-time, delayed streaming, intraday updates, and meticulously curated end-of-day pricing information.

Context

Bitcoin is the longest running and most well known cryptocurrency, first released as open source in 2009 by the anonymous Satoshi Nakamoto. Bitcoin serves as a decentralized medium of digital exchange, with transactions verified and recorded in a public distributed ledger (the blockchain) without the need for a trusted record keeping authority or central intermediary. Transaction blocks contain a SHA-256 cryptographic hash of previous transaction blocks, and are thus "chained" together, serving as an immutable record of all transactions that have ever occurred. As with any currency/commodity on the market, bitcoin trading and financial instruments soon followed public adoption of bitcoin and continue to grow. Included here is historical bitcoin market data for select bitcoin exchanges where trading takes place. Happy (data) mining!

CSV files for select bitcoin exchanges for the time period of September 2011 to June 2024, with updates of OHLC (Open, High, Low, Close), Volume in BTC and indicated currency, and weighted bitcoin price. Timestamps are in Unix time. Timestamps without any trades or activity have their data fields filled with NaNs. If a timestamp is missing, or if there are jumps, this may be because the exchange (or its API) was down, the exchange (or its API) did not exist, or some other unforeseen technical error in data reporting or gathering. All effort has been made to deduplicate entries and verify the contents are correct and complete to the best of my ability, but obviously trust at your own risk.

Acknowledgements and Inspiration

Bitcoin charts for the data. The various exchange APIs, for making it difficult or unintuitive enough to get OHLC and volume data that I set out on this data scraping project. Satoshi Nakamoto and the novel core concept of the blockchain, as well as its first execution via the bitcoin protocol. I'd also like to thank viewers like you! Can't wait to see what code or insights you all have to share.

Dataset from Monetary Authority of Singapore. For more information, visit https://data.gov.sg/datasets/d_046ff8d521a218d9178178cfbfc45c2c/view

I am a new developer and I would greatly appreciate your support. If you find this dataset helpful, please consider giving it an upvote!

Key Features:

Complete 1m Data: Raw 1m historical data from multiple exchanges, covering the entire trading history of ETHUSD available through their API endpoints. This dataset is updated daily to ensure up-to-date coverage.

Combined Index Dataset: A unique feature of this dataset is the combined index, which is derived by averaging all other datasets into one, please see attached notebook. This creates the longest continuous, unbroken ETHUSD dataset available on Kaggle, with no gaps and no erroneous values. It gives a much more comprehensive view of the market i.e. total volume across multiple exchanges.

Superior Performance: The combined index dataset has demonstrated superior 'mean average error' (MAE) metric performance when training machine learning models, compared to single-source datasets by a whole order of MAE magnitude.

Unbroken History: The combined dataset's continuous history is a valuable asset for researchers and traders who require accurate and uninterrupted time series data for modeling or back-testing.

https://i.imgur.com/5ti89wM.png" alt="ETHUSD Dataset Summary">

https://i.imgur.com/DnpNF9R.png" alt="Combined Dataset Close Plot"> This plot illustrates the continuity of the dataset over time, with no gaps in data, making it ideal for time series analysis.

Included Resources:

Two Notebooks:

Dataset Usage and Diagnostics: This notebook demonstrates how to use the dataset and includes a powerful data diagnostics function, which is useful for all time series analyses.

Aggregating Multiple Data Sources: This notebook walks you through the process of combining multiple exchange datasets into a single, clean dataset. (Currently unavailable, will be added shortly)

Cryptocurrency historical datasets from January 2012 (if available) to October 2021 were obtained and integrated from various sources and Application Programming Interfaces (APIs) including Yahoo Finance, Cryptodownload, CoinMarketCap, various Kaggle datasets, and multiple APIs. While these datasets used various formats of time (e.g., minutes, hours, days), in order to integrate the datasets days format was used for in this research study. The integrated cryptocurrency historical datasets for 80 cryptocurrencies including but not limited to Bitcoin (BTC), Ethereum (ETH), Binance Coin (BNB), Cardano (ADA), Tether (USDT), Ripple (XRP), Solana (SOL), Polkadot (DOT), USD Coin (USDC), Dogecoin (DOGE), Tron (TRX), Bitcoin Cash (BCH), Litecoin (LTC), EOS (EOS), Cosmos (ATOM), Stellar (XLM), Wrapped Bitcoin (WBTC), Uniswap (UNI), Terra (LUNA), SHIBA INU (SHIB), and 60 more cryptocurrencies were uploaded in this online Mendeley data repository. Although the primary attribute of including the mentioned cryptocurrencies was the Market Capitalization, a subject matter expert i.e., a professional trader has also guided the initial selection of the cryptocurrencies by analyzing various indicators such as Relative Strength Index (RSI), Moving Average Convergence/Divergence (MACD), MYC Signals, Bollinger Bands, Fibonacci Retracement, Stochastic Oscillator and Ichimoku Cloud. The primary features of this dataset that were used as the decision-making criteria of the CLUS-MCDA II approach are Timestamps, Open, High, Low, Closed, Volume (Currency), % Change (7 days and 24 hours), Market Cap and Weighted Price values. The available excel and CSV files in this data set are just part of the integrated data and other databases, datasets and API References that was used in this study are as follows: [1] https://finance.yahoo.com/ [2] https://coinmarketcap.com/historical/ [3] https://cryptodatadownload.com/ [4] https://kaggle.com/philmohun/cryptocurrency-financial-data [5] https://kaggle.com/deepshah16/meme-cryptocurrency-historical-data [6] https://kaggle.com/sudalairajkumar/cryptocurrencypricehistory [7] https://min-api.cryptocompare.com/data/price?fsym=BTC&tsyms=USD [8] https://min-api.cryptocompare.com/ [9] https://p.nomics.com/cryptocurrency-bitcoin-api [10] https://www.coinapi.io/ [11] https://www.coingecko.com/en/api [12] https://cryptowat.ch/ [13] https://www.alphavantage.co/

This dataset is part of the CLUS-MCDA (Cluster analysis for improving Multiple Criteria Decision Analysis) and CLUS-MCDAII Project: https://aimaghsoodi.github.io/CLUSMCDA-R-Package/ https://github.com/Aimaghsoodi/CLUS-MCDA-II https://github.com/azadkavian/CLUS-MCDA

The dataset is an extract of the Binance trading platform using the public REST API. It contains data covering the btcusdt historical market data for the year 2022, using the monthly chart frame. It's ideal for analysts who want a quick peek at historical crypto trading data for data exploration.

The Currency Composition ofOfficial Foreign Exchange Reserves(COFER) database is managed by the Statistics Department of the International Monetary Fund (IMF). The COFER website disseminates end-of-period quarterly data on COFER in the format of statistical aggregates. The currencies identified in COFER are: U.S. dollar, Pound sterling, Japanese yen, Swiss francs, Canadian dollar, Australian dollar, and Euro. All other currencies are indistinguishably included in the category of “other currencies.” Prior to the introduction of Euro in 1999,several European currencieswere separately identified in COFER. COFER data are reported to the IMF on a voluntary and confidential basis. COFER data for individual countries are strictly confidential. The data published on this website are aggregates for each currency for three groupings of countries (total,advanced economies, andemerging and developing economies).

List of currencies and their 3 digit codes as defined by ISO 4217. The data provided here is the consolidation of Table A.1 "Current currency & funds code list" and Table A.3 "Historic denominatio...

This dataset provides values for API CRUDE OIL STOCK CHANGE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Coal fell to 114.90 USD/T on August 1, 2025, down 0.22% from the previous day. Over the past month, Coal's price has risen 2.77%, but it is still 19.40% lower than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Coal - values, historical data, forecasts and news - updated on August of 2025.