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This dataset includes daily historical price data for Bitcoin (BTC-USD) from 2014 to 2025, obtained through web scraping from the Yahoo Finance page using Selenium. The primary data source can be accessed at Yahoo Finance - Bitcoin Historical Data . The dataset contains daily information such as opening price (Open), highest price (High), lowest price (Low), closing price (Close), adjusted closing price (Adj Close), and trading volume (Volume).

About Bitcoin: Bitcoin (BTC) is the world's first decentralized digital currency, introduced in 2009 by an anonymous creator known as Satoshi Nakamoto. It operates on a peer-to-peer network powered by blockchain technology, enabling secure, transparent, and trustless transactions without the need for intermediaries like banks. Bitcoin's limited supply of 21 million coins and its growing adoption have made it a popular asset for investment, trading, and as a hedge against inflation.

We are excited to share this dataset and look forward to seeing the insights it can provide. We hope it will inspire collaboration and innovation within the community. By leveraging this daily data, we can explore trends, develop predictive models, and design innovative trading strategies that deepen our understanding of Bitcoin's market behavior. Together, we can unlock new opportunities and contribute to the collective advancement of cryptocurrency research and analysis.

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

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.

CoinAPI's Flat Files S3 API delivers historical crypto market data through downloadable CSV files. Access trades, quotes, and order book information in a user-friendly format. Our readable data files provide everything universities and analytics companies need.

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)

Browse Options on Bitcoin Futures (BTC) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

The CME Group Market Data Platform (MDP) 3.0 disseminates event-based bid, ask, trade, and statistical data for CME Group markets and also provides recovery and support services for market data processing. MDP 3.0 includes the introduction of Simple Binary Encoding (SBE) and Event Driven Messaging to the CME Group Market Data Platform. Simple Binary Encoding (SBE) is based on simple primitive encoding, and is optimized for low bandwidth, low latency, and direct data access. Since March 2017, MDP 3.0 has changed from providing aggregated depth at every price level (like CME's legacy FAST feed) to providing full granularity of every order event for every instrument's direct book. MDP 3.0 is the sole data feed for all instruments traded on CME Globex, including futures, options, spreads and combinations. Note: We classify exchange-traded spreads between futures outrights as futures, and option combinations as options.

Origin: Directly captured at Aurora DC3 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, TBBO, Trades, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Statistics Learn more

Resolution: Immediate publication, nanosecond-resolution timestamps

Context

Bitcoin and other cryptocurrencies have captured the imagination of technologists, financiers, and economists. Digital currencies are only one application of the underlying blockchain technology. Like its predecessor, Bitcoin, the Ethereum blockchain can be described as an immutable distributed ledger. However, creator Vitalik Buterin also extended the set of capabilities by including a virtual machine that can execute arbitrary code stored on the blockchain as smart contracts.

Both Bitcoin and Ethereum are essentially OLTP databases, and provide little in the way of OLAP (analytics) functionality. However the Ethereum dataset is notably distinct from the Bitcoin dataset:

• The Ethereum blockchain has as its primary unit of value Ether, while the Bitcoin blockchain has Bitcoin. However, the majority of value transfer on the Ethereum blockchain is composed of so-called tokens. Tokens are created and managed by smart contracts.

• Ether value transfers are precise and direct, resembling accounting ledger debits and credits. This is in contrast to the Bitcoin value transfer mechanism, for which it can be difficult to determine the balance of a given wallet address.

• Addresses can be not only wallets that hold balances, but can also contain smart contract bytecode that allows the programmatic creation of agreements and automatic triggering of their execution. An aggregate of coordinated smart contracts could be used to build a decentralized autonomous organization.

Content

The Ethereum blockchain data are now available for exploration with BigQuery. All historical data are in the ethereum_blockchain dataset, which updates daily.

Our hope is that by making the data on public blockchain systems more readily available it promotes technological innovation and increases societal benefits.

Querying BigQuery tables

You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at bigquery-public-data.crypto_ethereum.[TABLENAME]. Fork this kernel to get started.

Acknowledgements

Cover photo by Thought Catalog on Unsplash

Inspiration

• What are the most popularly exchanged digital tokens, represented by ERC-721 and ERC-20 smart contracts?
• Compare transaction volume and transaction networks over time
• Compare transaction volume to historical prices by joining with other available data sources like Bitcoin Historical Data

Browse Bitwise Bitcoin ETF (BITB) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

Nasdaq TotalView-ITCH is the proprietary data feed that provides full order book depth for Nasdaq market participants.

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

A cryptocurrency, crypto-currency, or crypto is a collection of binary data which is designed to work as a medium of exchange. Individual coin ownership records are stored in a ledger, which is a computerized database using strong cryptography to secure transaction records, to control the creation of additional coins, and to verify the transfer of coin ownership. Cryptocurrencies are generally fiat currencies, as they are not backed by or convertible into a commodity. Some crypto schemes use validators to maintain the cryptocurrency. In a proof-of-stake model, owners put up their tokens as collateral. In return, they get authority over the token in proportion to the amount they stake. Generally, these token stakes get additional ownership in the token overtime via network fees, newly minted tokens, or other such reward mechanisms.

Cryptocurrency does not exist in physical form (like paper money) and is typically not issued by a central authority. Cryptocurrencies typically use decentralized control as opposed to a central bank digital currency (CBDC). When a cryptocurrency is minted or created prior to issuance or issued by a single issuer, it is generally considered centralized. When implemented with decentralized control, each cryptocurrency works through distributed ledger technology, typically a blockchain, that serves as a public financial transaction database

A cryptocurrency is a tradable digital asset or digital form of money, built on blockchain technology that only exists online. Cryptocurrencies use encryption to authenticate and protect transactions, hence their name. There are currently over a thousand different cryptocurrencies in the world, and many see them as the key to a fairer future economy.

Bitcoin, first released as open-source software in 2009, is the first decentralized cryptocurrency. Since the release of bitcoin, many other cryptocurrencies have been created.

Content

This Dataset is a collection of records of 3000+ Different Cryptocurrencies. * Top 395+ from 2021 * Top 3000+ from 2023

Structure of the Dataset

https://i.imgur.com/qGVJaHl.png" alt="">

Acknowledgements

This Data is collected from: https://finance.yahoo.com/. If you want to learn more, you can visit the Website.

Cover Photo by Worldspectrum: https://www.pexels.com/photo/ripple-etehereum-and-bitcoin-and-micro-sdhc-card-844124/

Browse iShares Bitcoin Trust (IBIT) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

Nasdaq TotalView-ITCH is the proprietary data feed that provides full order book depth for Nasdaq market participants.

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

Browse Fidelity Wise Origin Bitcoin Fund (FBTC) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

Nasdaq TotalView-ITCH is the proprietary data feed that provides full order book depth for Nasdaq market participants.

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

Browse ProShares Bitcoin Strategy ETF (BITO) 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

Browse 2x Bitcoin Strategy ETF (BITX) 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

Browse Micro Bitcoin Futures (MBT) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

The CME Group Market Data Platform (MDP) 3.0 disseminates event-based bid, ask, trade, and statistical data for CME Group markets and also provides recovery and support services for market data processing. MDP 3.0 includes the introduction of Simple Binary Encoding (SBE) and Event Driven Messaging to the CME Group Market Data Platform. Simple Binary Encoding (SBE) is based on simple primitive encoding, and is optimized for low bandwidth, low latency, and direct data access. Since March 2017, MDP 3.0 has changed from providing aggregated depth at every price level (like CME's legacy FAST feed) to providing full granularity of every order event for every instrument's direct book. MDP 3.0 is the sole data feed for all instruments traded on CME Globex, including futures, options, spreads and combinations. Note: We classify exchange-traded spreads between futures outrights as futures, and option combinations as options.

Origin: Directly captured at Aurora DC3 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, TBBO, Trades, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Statistics Learn more

Resolution: Immediate publication, nanosecond-resolution timestamps

Browse iShares Ethereum Trust ETF (ETHA) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

Nasdaq TotalView-ITCH is the proprietary data feed that provides full order book depth for Nasdaq market participants.

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