In March 2024 Bitcoin BTC reached a new all-time high with prices exceeding 73000 USD marking a milestone for the cryptocurrency market This surge was due to the approval of Bitcoin exchange-traded funds ETFs in the United States allowing investors to access Bitcoin without directly holding it This development increased Bitcoin’s credibility and brought fresh demand from institutional investors echoing previous price surges in 2021 when Tesla announced its 15 billion investment in Bitcoin and Coinbase was listed on the Nasdaq By the end of 2022 Bitcoin prices dropped sharply to 15000 USD following the collapse of cryptocurrency exchange FTX and its bankruptcy which caused a loss of confidence in the market By August 2024 Bitcoin rebounded to approximately 64178 USD but remained volatile due to inflation and interest rate hikes Unlike fiat currency like the US dollar Bitcoin’s supply is finite with 21 million coins as its maximum supply By September 2024 over 92 percent of Bitcoin had been mined Bitcoin’s value is tied to its scarcity and its mining process is regulated through halving events which cut the reward for mining every four years making it harder and more energy-intensive to mine The next halving event in 2024 will reduce the reward to 3125 BTC from its current 625 BTC The final Bitcoin is expected to be mined around 2140 The energy required to mine Bitcoin has led to criticisms about its environmental impact with estimates in 2021 suggesting that one Bitcoin transaction used as much energy as Argentina Bitcoin’s future price is difficult to predict due to the influence of large holders known as whales who own about 92 percent of all Bitcoin These whales can cause dramatic market swings by making large trades and many retail investors still dominate the market While institutional interest has grown it remains a small fraction compared to retail Bitcoin is vulnerable to external factors like regulatory changes and economic crises leading some to believe it is in a speculative bubble However others argue that Bitcoin is still in its early stages of adoption and will grow further as more institutions and governments recognize its potential as a hedge against inflation and a store of value 2024 has also seen the rise of Bitcoin Layer 2 technologies like the Lightning Network which improve scalability by enabling faster and cheaper transactions These innovations are crucial for Bitcoin’s wider adoption especially for day-to-day use and cross-border remittances At the same time central bank digital currencies CBDCs are gaining traction as several governments including China and the European Union have accelerated the development of their own state-controlled digital currencies while Bitcoin remains decentralized offering financial sovereignty for those who prefer independence from government control The rise of CBDCs is expected to increase interest in Bitcoin as a hedge against these centralized currencies Bitcoin’s journey in 2024 highlights its growing institutional acceptance alongside its inherent market volatility While the approval of Bitcoin ETFs has significantly boosted interest the market remains sensitive to events like exchange collapses and regulatory decisions With the limited supply of Bitcoin and improvements in its transaction efficiency it is expected to remain a key player in the financial world for years to come Whether Bitcoin is currently in a speculative bubble or on a sustainable path to greater adoption will ultimately be revealed over time.

The following dataset contains the attributes: Date: Specific date to be observed for the corresponding price. Open: The opening price for the day High: The maximum price it has touched for the day Low: The minimum price it has touched for the day Close: The closing price for the day percent_change_24h: Percentage change for the last 24hours Volume: Volume of Bitcoin traded at the date Market Cap: Market Value of traded Bitcoin

1) Data Introduction • The Bitcoin Historical Dataset is a cryptocurrency time-series dataset that summarizes the history of Bitcoin (BTC) minutes-by-minute transactions in a tabular format for 2017, including key transaction information such as market price and volume per minute.

2) Data Utilization (1) Bitcoin Historical Dataset has characteristics that: • Each row contains key market and transaction information, including Unix timestamps, dates (UTC), symbols, open, high, low, close, BTC, and USD. • The data is an ultra-high resolution time series structure that is well structured for price volatility analysis, ultra-short prediction, deep learning time series model learning, and more. (2) Bitcoin Historical Dataset can be used to: • Bitcoin Price Forecasting and Trading Strategies: Using minute-by-minute market price data, it can be used to develop deep learning-based price forecasting and auto-trading strategies such as LSTM and reinforcement learning. • Analyzing Volatility and Market Patterns: High-frequency trading data can be applied to researching cryptocurrency market structure, including market volatility, detection of abnormal trading, and transaction volume-based pattern analysis.

About this Dataset

This dataset contains the prices of Bitcoin every minute over a period from 2017-11-06 03:00 to 2023-03-10 2:59 (YYYY-MM-DD). The data includes the time, close time, open, high, low, close prices, the volume exchanged per minute and the number of trades per minute. It represent Bitcoin prices over 2.8 millions values. This dataset is ideal for anyone who want to track, study and analyze BTC/USDT values over more than 5 years.

Time range: From 2017-11-06 04:00 to 2023-03-40 14:00

File format: Datas are in .csv format

Columns values: - time: Date in milliseconds where observation begins - open: Opening ETH price in the minute - high: Highest ETH price in the minute - low: Lowest ETH price in the minute - close: Closing ETH price in the minute - volume: Volume exchanges between time and close_time - close_time: Date in milliseconds were observation ends

Category

Economic

Keywords

Bitcoin,BTC,#btc,Cryptocurrency,Crypto

Row Count

2808000

Price

$149.00

Any form of currency that only exists digitally relying on cryptography to prevent counterfeiting and fraudulent transactions is defined as cryptocurrency. Bitcoin was the very first Cryptocurrency. It was invented in 2009 by an anonymous person, or group of people, who referred to themselves as Satoshi Nakamoto. When someone sends a bitcoin (or a fraction of a bitcoin) to someone else, “miners” record that transaction in a block and add the transaction to a digital ledger. These blocks are collectively known as the blockchain – an openly accessible ledger of every transaction ever made in bitcoin. Blockchains are distributed across many computers so that the record of transactions cannot be altered. Only 21 million bitcoins can ever be mined and about 17 million have been mined so far. Bitcoin is mined, or created, by people (miners) getting their computers to solve mathematical problems, in order to update and verify the ledger.

The value of bitcoin is determined by what people are willing to pay for it, and is very volatile, fluctuating wildly from day to day. In April 2013, the value of 1 bitcoin (BTC) was around $100 USD. At the beginning of 2017 its value was $1,022 USD and by the 15th of December it was worth $19,497. As of the 3rd of March 2018, 1 BTC sells for $11,513 USD. So, the time series analysis of bitcoin series is very challenging.

The following dataset is the daily closing price of bitcoin from the 27th of April 2013 to the 3rd of March 2018. Source: coinmarketcap.com

The dataset is focused on has gathered from coinmarketcap.com (https://coinmarketcap.com/). includes he daily closing price of bitcoin from the 27th of April 2013 to the 3rd of March 2018 and is available in the csv file Bitcoin_Historical_Price.csv

This Model includes a mean absolute scaled error (MASE), for each of model fits and forecasts. Using the real values of daily bitcoin for 10 days of forecast period (4th - 13th of March 2018).

This model is used to analyze the data, accurately predict the value of bitcoin for the next 10 days. The model includes descriptive analysis, proper visualization, model specification, model fitting and selection, and diagnostic checking.

Context🔥

This is a Dataset that represent bitcoin prices in 2015-2021

Content✔️

we have open, close, low and high prices in usd. the dates(open, close) also exists in this csv file. API that I got the results of is CoinAPI: with free plan you can access rest api i put the link below so you can also use it.

https://www.coinapi.io/

Acknowledgements

I just want to thank CoinAPI this amazing service. if you liked it I will be happy if you vote up it and follow my kaggle profile.😃

In this work, i will be analyzing the Bitcoin growth trends from January 2012 to March 2021 in comparison with year indicators where Bitcoin usages/patronage, volumes and prices were high and low across the world.

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

that is to say

Context

Things like Block chain, Bitcoin, Bitcoin cash, Ethereum, Ripple etc are constantly coming in the news articles I read. So I wanted to understand more about it and this post helped me get started. Once the basics are done, the data scientist inside me started raising questions like:

How many cryptocurrencies are there and what are their prices and valuations? Why is there a sudden surge in the interest in recent days? So what next? Now that we have the price data, I wanted to dig a little more about the factors affecting the price of coins. I started of with Bitcoin and there are quite a few parameters which affect the price of Bitcoin. Thanks to Blockchain Info, I was able to get quite a few parameters on once in two day basis.

This will help understand the other factors related to Bitcoin price and also help one make future predictions in a better way than just using the historical price.

Content

The dataset has one csv file for each currency. Price history is available on a daily basis from April 28, 2013. This dataset has the historical price information of some of the top crypto currencies by market capitalization.

Date : date of observation Open : Opening price on the given day High : Highest price on the given day Low : Lowest price on the given day Close : Closing price on the given day Volume : Volume of transactions on the given day

OHLCV is an abbreviation for the five critical data points: Open, High, Low, Close, and Volume. It refers to the key points in analyzing an asset such as Bitcoin (BTC) in the market over a specified time. The dataset is important for not only traders and analysts but also for data scientists who work on BTC market prediction using artificial intelligence. The 'Open' and 'Close' prices represent the starting and ending price levels, while the 'High' and 'Low' are the highest and lowest prices during that period (a daily time frame (24h)). The 'Volume' is a measure of the total number of trades. This dataset provides five OHLCV data columns for BTC along with a column called "Next day close price" for regression problems and machine learning applications. The dataset includes daily information from 1/1/2012 to 8/6/2022.

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 at 1-min intervals for select bitcoin exchanges where trading takes place.

Content

This dataset includes Bitcoin's opening price, closing price, lowest value, highest value, market volume and market cap information between December 2013 and December 2021.

Bitcoin's circulating supply has grown steadily since its inception in 2009, reaching over 19.93 million coins by early October 2025. This gradual increase reflects the cryptocurrency's design, which put a limit of 21 million on the total number of bitcoins that can ever exist. This impacts the Bitcoin price somewhat, as its scarcity can lead to volatility on the market. Maximum supply and scarcity Bitcoin is unusual from other cryptocurrencies in that its maximum supply is getting closer. By October 2025, more than 90 percent of all possible Bitcoin had been created. That said, Bitcoin's circulating supply is expected to reach its maximum around the year 2140. Meanwhile, mining becomes exponentially more difficult and energy-intensive. Institutional investors In 2025, countries like the United States openly started discussing the possibility of buying bitcoins to hold in reserve. By the time of writing, it was unclear whether this would happen. Nevertheless, institutional investors displayed more interest in the cryptocurrency than before. Certain companies owned several thousands of Bitcoin tokens in 2025, for example. This and the limited number of Bitcoin may further fuel price volatility.

Key Features

How to use this dataset

1. Market Analysis: Use the dataset to conduct in-depth market analysis by observing trends in price fluctuations (24h, 1h, 7d) across different cryptocurrencies. Identify correlations between changes in price and other factors like market capitalization and trading volume.

2. Ranking and Comparison: Leverage the rank attribute to compare and contrast cryptocurrencies based on their market cap, price, and percentage changes. Analyze the performance of different cryptocurrencies over various timeframes.

3. Supply Analysis: Study the supply-related attributes such as circulating supply, total supply, and maximum supply to assess the scarcity and potential growth of specific cryptocurrencies. Understand the implications of limited versus unlimited supply currencies on their value.

4. Trading Volume Insights: Explore the relationship between price changes and trading volume (both current and historical). Analyze how trading volume impacts price fluctuations and overall market behavior for each cryptocurrency.

5. Predictive Modeling: Utilize this dataset as a foundation for predictive modeling or forecasting cryptocurrency prices. Apply machine learning algorithms or statistical methods to predict potential price movements based on historical data and patterns.

If you find this dataset useful, give it an upvote – it's a small gesture that goes a long way! Thanks for your support. 😄

This dataset is about cryptos per day. It has 1 row and is filtered where the crypto is Dogecoin and the date is the 8th of May 2025. It features 3 columns: date, and highest price.

Context

In the last few days, I have been hearing a lot of buzz around cryptocurrencies. Things like Block chain, Bitcoin, Bitcoin cash, Ethereum, Ripple etc are constantly coming in the news articles I read. So I wanted to understand more about it and this post helped me get started. Once the basics are done, the DS guy sleeping inside me (always lazy.!) woke up and started raising questions like

1. How many such cryptocurrencies are there and what are their prices and valuations?
2. Why is there a sudden surge in the interest in recent days? Is it due to the increase in the price in the last few days? etc.

For getting answers to all these questions (and if possible to predict the future prices ;)), I started getting the data from coinmarketcap about the cryptocurrencies.

Content

This dataset has the historical price information of some of the top cryptocurrencies by market capitalization. The currencies included are

• Bitcoin
• Ethereum
• Ripple
• Bitcoin cash
• Bitconnect
• Dash
• Ethereum Classic
• Iota
• Litecoin
• Monero
• Nem
• Neo
• Numeraire
• Stratis
• Waves

In case if you are interested in the prices of some other currencies, please post in comments section and I will try to add them in the next version. I am planning to revise it once in a week.

Dataset has one csv file for each currency. Price history is available on a daily basis from April 28, 2013 till Aug 07, 2017. The columns in the csv file are

• Date : date of observation
• Open : Opening price on the given day
• High : Highest price on the given day
• Low : Lowest price on the given day
• Close : Closing price on the given day
• Volume : Volume of transactions on the given day
• Market Cap : Market capitalization in USD

Acknowledgements

This data is taken from coinmarketcap and it is free to use the data.

Cover Image : Photo by Thomas Malama on Unsplash

Inspiration

Some of the questions which could be inferred from this dataset are:

1. How did the historical prices / market capitalizations of various currencies change over time?
2. Predicting the future price of the currencies
3. Which currencies are more volatile and which ones are more stable?
4. How does the price fluctuations of currencies correlate with each other?
5. Seasonal trend in the price fluctuations

Bitcoin yearly price prediction dataset covering 2025 to 2050 with minimum and maximum forecast values.

This dataset provides comprehensive historical data on Bitcoin, a leading cryptocurrency in the digital finance space. The dataset covers a range of key aspects, including daily price movements, market trends, trading volumes, and additional relevant metrics. It is a valuable resource for researchers, analysts, and enthusiasts interested in gaining insights into Bitcoin's market behavior and performance over time.

Key Features:

Date: The date of the recorded data points. Open: The opening price of Bitcoin on a given day. High: The highest price reached during the day. Low: The lowest price reached during the day. Close: The closing price of Bitcoin on a given day. Total Trade Quantity: The total quantity of Bitcoin traded on a given day. Turnover (Lacs): The total turnover (value of all trades) in Bitcoin.

Column Profiling:

Date: This column contains temporal data representing the date of each recorded observation. It is likely a datetime format and may exhibit a time series pattern.

Open, High, Low, Close: These columns represent the price levels of Bitcoin at different points in a trading day. They are continuous numerical variables and may have fluctuations and trends.

Total Trade Quantity: This column represents the total quantity of Bitcoin traded. It is a continuous numerical variable indicating market activity and liquidity.

Turnover (Lacs): This column represents the total turnover in Bitcoin, providing insights into the overall value of trading activity.

Explore this dataset to perform in-depth analyses, create predictive models, or derive actionable insights related to Bitcoin's market dynamics.

Investment cannot be separated from the level of return and risk inherent in assets. Today, investment instruments are not only stocks, currencies, bonds, deposits, savings and others. The beginning of Bitcoin’s emergence as a pioneer of Cryptocurrency was in 2009. Crypto assets are emerging rapidly and are accompanied by an increase in the number of transactions each period. The growth in the market capitalization value of crypto assets has also grown significantly. During COVID-19, many investments, such as stocks, experienced a decline due to market uncertainty. The results of this study prove that with the existence of COVID-19, the crypto market is not affected. Crypto is an attraction characterized by a high degree of fluctuation, and there is no limit to transactions in the open market 24 hours to trade. The Cryptocurrency market is currently a market that can provide short-term benefits to risk-taking investors, while the market in other investment instruments is declining. 78% of the value capitalization of the top 200 cryptocurrencies is represented by the top 9 cryptos used as samples in this study. So that if there is a decrease in these 9 cryptos, it will also have an impact on the overall capitalization value of crypto in the market. The future development of Cryptocurrencies will no longer be digital assets traded with many speculators who can control prices, it can even be digital money that can be used worldwide without any transaction fees and is controlled on a blockchain system. (2023-01-12)

This dataset contains the predicted prices of the asset Bitcoin over the next 16 years. This data is calculated initially using a default 5 percent annual growth rate, and after page load, it features a sliding scale component where the user can then further adjust the growth rate to their own positive or negative projections. The maximum positive adjustable growth rate is 100 percent, and the minimum adjustable growth rate is -100 percent.