View daily updates and historical trends for Bitcoin Price. Source: CoinGecko. Track economic data with YCharts analytics.

This dataset is curated for those who are interested in predicting Bitcoin prices using historical data. It contains comprehensive information on Bitcoin's market behavior over time, including daily prices, trading volumes, and other relevant financial indicators. This dataset can be used to develop and test predictive models, analyze trends, and gain insights into the cryptocurrency market.

Features: Date: The date corresponding to each entry. Open: The opening price of Bitcoin for the given date. High: The highest price reached by Bitcoin on the given date. Low: The lowest price reached by Bitcoin on the given date. Close: The closing price of Bitcoin for the given date. Volume: The total volume of Bitcoin traded on the given date. Market Cap: The total market capitalization of Bitcoin on the given date. Adjusted Close: The closing price adjusted for any dividends or stock splits. Usage: This dataset can be used for various purposes, including:

Time Series Analysis: Understanding how Bitcoin prices fluctuate over time. Predictive Modeling: Building models to predict future prices based on historical data. Market Research: Analyzing trends and patterns in the cryptocurrency market.

Historical Bitcoin to USD Price Dataset (Up to 01.09.2023)

Description: Unlock valuable insights into the dynamic world of cryptocurrency with our comprehensive Historical Bitcoin to USD Price Dataset. This meticulously curated dataset spans from the inception of Bitcoin up until September 1st, 2023, offering a deep dive into the evolution of its market value over time.

Comprising meticulously collected and cleaned data, this dataset empowers researchers, analysts, and enthusiasts to explore the nuances of Bitcoin's price trends, market fluctuations, and potential patterns. Whether you're an experienced data scientist seeking to uncover intricate correlations or a curious novice eager to understand Bitcoin's journey, this dataset provides an invaluable resource.

Key Features:

Time Frame: Historical data ranging from the earliest Bitcoin prices to September 1st, 2023.
Granularity: Daily price points capturing the nuances of price fluctuations over the years.
Market Dynamics: Explore the impact of major events on Bitcoin's price, including halving events, regulatory developments, and macroeconomic shifts.
Research-Ready: Cleaned and pre-processed data to minimize hassle and maximize research efficiency.
Versatile Usage: Suitable for time series analysis, predictive modeling, data visualization, and more.
Format: CSV files for seamless integration into various data analysis tools and programming languages.

Whether you're building predictive models, conducting market research, or seeking historical context for your crypto-related endeavors, this dataset equips you with the tools to derive meaningful insights from Bitcoin's fascinating journey to date. Embark on your data-driven exploration today.

(Note: The actual dataset content and structure details need to be prepared according to your data and specifications.)

Bitcoin price data for 2025-11-06 including currency, value, high, low, open, close, and percentage difference.

Subtitle:

Comprehensive Bitcoin Hourly Trading Dataset: 2017–2024

Description:

This dataset offers detailed hourly trading data for Bitcoin (BTC-USD), covering the period from August 17, 2017, to December 25, 2024. It is sourced from Binance, one of the most prominent cryptocurrency exchanges, and is designed to provide a granular view of Bitcoin's market activity over several years.

Dataset Highlights:

• Timeframe: Over seven years of hourly data for in-depth analysis of market trends.
• OHLC Data: Includes Open, High, Low, and Close prices, enabling detailed candlestick analysis.
• Trading Volume: Captures the total traded volume for each hour, aiding in liquidity analysis.
• Quote Asset Volume: Represents the traded volume in USD equivalent, facilitating fiat comparisons.
• Number of Trades: The count of trades executed within each hour, offering insights into market activity.
• Taker Buy Base/Quote Volumes: Differentiates between aggressive (taker) buy orders in both Bitcoin and USD equivalents.
• Close Time: Marks the precise end of each hourly interval for temporal accuracy.

Applications:

This dataset is an excellent resource for:
- Time-Series Analysis: Understanding long-term and short-term market trends.
- Machine Learning Models: Training models for price prediction, anomaly detection, or volatility analysis.
- Algorithmic Trading: Building and backtesting trading strategies.
- Market Research: Analyzing Bitcoin's market dynamics, trading behavior, and historical performance.

The dataset is particularly useful for crypto enthusiasts, data scientists, and financial analysts seeking to explore the nuances of Bitcoin's price movements and trading activity 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

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 1h Data: Raw 1h historical data from multiple exchanges, covering the entire trading history of BTCUSD 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 BTCUSD 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/OVOyF5A.png" alt="BTCUSD Dataset Summary">

https://i.imgur.com/6hxG2G3.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)

Based on professional technical analysis and AI models, deliver precise price‑prediction data for Bitcoin on 2025-10-31. Includes multi‑scenario analysis (bullish, baseline, bearish), risk assessment, technical‑indicator insights and market‑trend forecasts to help investors make informed trading decisions and craft sound investment strategies.

https://azcoinnews.com/wp-content/uploads/2021/01/bitcoin-price-hit-42000-amid-rising-interest-in-btc-on-google-trends.jpg" alt="">

Bitcoin

Bitcoin (₿) is a decentralized digital currency, without a central bank or single administrator, that can be sent from user to user on the peer-to-peer bitcoin network without the need for intermediaries. Transactions are verified by network nodes through cryptography and recorded in a public distributed ledger called a blockchain. The cryptocurrency was invented in 2008 by an unknown person or group of people using the name Satoshi Nakamoto. The currency began to use in 2009 when its implementation was released as open-source software.

The Historical prices of Bitcoin have been added to the dataset for you to explore :

Bitcoin Historical data (2010-2022).csv

Google Trends

Google Trends is a website by Google that analyzes the popularity of top search queries in Google Search across various regions and languages. The website uses graphs to compare the search volume of different queries over time.

On August 5, 2008, Google launched Google Insights for Search, a more sophisticated and advanced service displaying search trends data. On September 27, 2012, Google merged Google Insights for Search into Google Trends.

The datasets consist of the following files, which were extracted from Google trends using pytrends package

• Bitcoin Trend across countries - Bitcoin trend among different countries
• Bitcoin Weekly trend - Bitcoin Interest over time
• Historical interest of Bitcoin (2016-2022) - Historical google trend of bitcoin from 2016 to 2022
• Rising bitcoin-related queries
• Top bitcoin-related queries
• Rising bitcoin-related topics
• Top bitcoin-related topics

Bitcoin Tweets

You could also integrate bitcoin tweets in order to enrich your analysis and understand the frenzy of bitcoin among people. The dataset is updated regularly and has more than 3.1 Million tweets by users.

Bitcoin tweets dataset: https://www.kaggle.com/datasets/kaushiksuresh147/bitcoin-tweets

Topics

• EDA On Bitcoin Prices
• Correlation between the bitcoin prices and the google trends
• Bitcoin google trend key performance indicators (KPIs)
• Bitcoin google trend plotly+dash dashboard

Acknowledgments

The dataset was extracted using pytrends python package to obtain the trend values from google trend across different countries and time.

The average energy consumption for one single Bitcoin transaction in 2025 could equal several hundreds of thousands of VISA card transactions. This according to a source that tries to estimate the energy consumption of both Bitcoin (BTC) over time. It does so by estimating how much income miners possibly spend on electricity, as there is no institution that tracks how much energy the cryptocurrency actually consumes. This also applies to which countries mine the most Bitcoin, as this is estimated by cross referencing IP addresses. A matter of design: why Bitcoin consumes so much energy Of all the 21 million Bitcoins that can exist at the same time, nearly 90 percent was already mined in mid-2021. This, however, does not necessarily mean that the Bitcoin supply is running out as the last Bitcoin was forecast to be mined around the year 2140. This is a design choice in the cryptocurrency: The closer Bitcoin gets to its supply limits, the computing power – and therefore energy - needed to mine goes up incrementally. The BTC mining difficulty or amount of computing power being applied to mine Bitcoin reflects that: Bitcoin mining in, say, 2014 – when there were less Bitcoin in circulation - was easier and less energy consuming than in 2021. By then, there were significantly more coins in circulation and the cryptocurrency’s design essentially tries to halt the creation of more. China’s doubts on whether Bitcoin is green Over the course of 2021, the price of Bitcoin was over 60,000 U.S. dollars but by the summer only half of that amount remained. This was partially caused by China’s Financial Stability and Development Committee trying to curb domestic crypto mining since May 2021 – which led some to doubt whether there was a future for the cryptocurrency. China’s efforts are said to have been triggered due to remote mining farms demanding so much electricity that idle coal mines were restarted without government approval. Whilst this was never confirmed, China is generally seen as the most coal consuming country in the world.

Prices for BTCBRL Bitcoin Brazilian Real including live quotes, historical charts and news. BTCBRL Bitcoin Brazilian Real was last updated by Trading Economics this December 1 of 2025.

Ethereum's price history suggests that that crypto was worth more in 2025 than during late 2021, although nowhere near the highest price recorded. Much like Bitcoin (BTC), the price of ETH went up in 2021 but for different reasons altogether: Ethereum, for instance, hit the news when a digital art piece was sold as the world's most expensive NFT for over 38,000 ETH - or 69.3 million U.S. dollars. Unlike Bitcoin, of which the price growth was fueled by the IPO of the U.S.'s biggest crypto trader, Coinbase, the rally on Ethereum came from technological developments that caused much excitement among traders. First, the so-called 'Berlin update' rolled out on the Ethereum network in April 2021, an update that would eventually lead to the Ethereum Merge in 2022 and reduced ETH gas prices - or reduced transaction fees. The collapse of FTX in late 2022, however, changed much for the cryptocurrency. As of November 13, 2025, Ethereum was worth 3,409.61 U.S. dollars - significantly less than the 4,400 U.S. dollars by the end of 2021.Ethereum's future and the DeFi industryPrice developments on Ethereum are difficult to predict but cannot be seen without the world of DeFi, or decentralized finance. This industry used technology to remove intermediaries between parties in a financial transaction. One example includes crypto wallets such as Coinbase Wallet that grew in popularity recently, with other examples including smart contractor Uniswap, Maker (responsible for stablecoin DAI), moneylender Dharma and market protocol Compound. Ethereum's future developments are tied with this industry: Unlike Bitcoin and Ripple, Ethereum is technically not a currency but an open-source software platform for blockchain applications, with Ether being the cryptocurrency that is used inside the Ethereum network. Essentially, Ethereum facilitates DeFi, meaning that if DeFi does well, so does Ethereum.NFTs: the most well-known application of EthereumNFTs or non-fungible tokens, grew nearly tenfold between 2018 and 2020, as can be seen in the market cap of NFTs worldwide. These digital blockchain assets can essentially function as a unique code connected to a digital file, allowing to distinguish the original file from any potential copies. This application is especially prominent in crypto art, although there are other applications: gaming, sports, and collectibles are other segments where NFT sales occur.

Introduction: The "Cryptocurrency Price Analysis Dataset: BTC, ETH, XRP, LTC (2018-2023)" is a comprehensive dataset that captures the daily price movements of six popular cryptocurrencies. It covers a period from January 1, 2018, to May 31, 2023, providing a valuable resource for researchers, analysts, and enthusiasts interested in studying the historical price behavior of these digital assets.

Description: This dataset contains a wealth of information for six major cryptocurrencies: Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), and Litecoin (LTC). The data spans a time frame of over five years, enabling users to explore long-term trends, analyze volatility patterns, and gain insights into market dynamics.

Columns:

1. Crypto: This column specifies the name of the cryptocurrency (e.g., BTC, ETH, XRP, LTC).
2. Date: The date on which the price data was recorded.
3. Open: The opening price of the cryptocurrency at the beginning of the day.
4. High: The highest price reached by the cryptocurrency during the day.
5. Low: The lowest price reached by the cryptocurrency during the day.
6. Close: The closing price of the cryptocurrency at the end of the day.

Use Cases: The dataset offers numerous possibilities for analysis and research within the field of cryptocurrencies. Here are a few potential use cases:

1. Price Analysis: Researchers can investigate the historical price movements of each cryptocurrency to identify trends, patterns, and potential correlations between different assets.
2. Volatility Study: The dataset enables the study of volatility in cryptocurrency markets, helping users understand the frequency and magnitude of price fluctuations.
3. Market Performance: Analysts can analyze the performance of individual cryptocurrencies over time, comparing returns and risk measures to assess their investment potential.
4. Trading Strategies: Traders can utilize the dataset to develop and backtest trading strategies based on technical indicators, price patterns, or machine learning algorithms.
5. Sentiment Analysis: Combine this dataset with external sentiment data to explore the relationship between market sentiment and cryptocurrency price movements. By sharing this dataset on Kaggle, you are providing a valuable resource to the data science community, encouraging collaborative research, and enabling the development of innovative models and solutions within the cryptocurrency domain.

Please note that this dataset is for educational and research purposes only and should not be used for making financial decisions without thorough analysis and consultation with financial professionals.

The selected variables were chosen base on the literature for time series of stock prices prediction or Forex (currency) prediction. The analises test only variables associated with the price like Bitcoin close, open, high and low price and volumn (for one representative exchange). Like Chen and Bahar, we used moving average of the variables to generate new variables in order to capture other information that could be hidden due the high noise generate characteristic of a high volatile asset. Also, like \cite{Bahar2016}, we use Gold an Death Cross, that are very common data for technical analysis.

Prices for PKRBTC Pakistani Rupee Bitcoin including live quotes, historical charts and news. PKRBTC Pakistani Rupee Bitcoin was last updated by Trading Economics this December 2 of 2025.

Prices for BTCSOL Bitcoin Solana including live quotes, historical charts and news. BTCSOL Bitcoin Solana was last updated by Trading Economics this December 2 of 2025.

Prices for BTCTHB Bitcoin Thai Baht including live quotes, historical charts and news. BTCTHB Bitcoin Thai Baht was last updated by Trading Economics this December 3 of 2025.

Memecoin Shiba Inu saw its price grow by more than 300 percent within one and the same month, marking a trading fury reminiscent of Dogecoin in early 2021. Indeed, the SHIB coin ranked as one of the biggest crypto in the world based on 24h trading volume in October 2021 - with trading activity being almost as high as that of Ethereum. Originally starting out as a fun token based on the famous Japanese dog breed, the digital currency grabbed mainstream attention in 2021 probably due to its low barrier of entry: Even after its price spikes, Shiba Inu was one of the cheapest coins available, especially when compared to the price of 99 other cryptocurrencies. Combine this with survey information that most consumers in the U.S. and the UK invest in crypto either for growth or fun, and Shiba Inu is probably seen by many as a relatively simple, "quick win" investment. As of May 19, 2025, the price of one million Shiba Inu is 14.08.

Based on professional technical analysis and AI models, deliver precise price‑prediction data for Overtime on 2025-12-01. Includes multi‑scenario analysis (bullish, baseline, bearish), risk assessment, technical‑indicator insights and market‑trend forecasts to help investors make informed trading decisions and craft sound investment strategies.

Cryptocurrency Market size was valued at around USD 6.78 billion in 2024 and is projected to reach USD 15.03 billion by 2030 along with a CAGR of around 14.19%.