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CryptoSentiment is a dataset, which contains sentiment information about cryptocurrency assets, gathered by various online sources, and analyzed by FinBERT sentiment extractor. More specifically, we provide a publicly available dataset containing fine-grained sentiment analysis data (minute-basis) about cryptocurrency market collected by different online sources. CryptoSentiment dataset includes 235,907 sentiment scores for 14 different cryptocurrencies gathered from various online sources such as news articles and social media.
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Bitcoin Pulse is a curated dataset combining hourly crypto, macroeconomic, and sentiment indicators to help researchers and developers forecast Bitcoin price movements.
It brings together a wide range of features from:
🟢 Crypto markets: BTC, ETH, SOL, DOGE, and more
📈 Global indices: NASDAQ, S&P500, DAX, and others
🧠 Sentiment & psychology: Fear & Greed Index, Google Trends, BTC dominance
💹 Derivatives signals: Open interest, volatility metrics
⏱️ Hourly frequency, fully filled, aligned, and ready for time series modeling
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.
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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)
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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
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The Report Covers Global Crypto Market Analysis & Trends. Cryptocurrencies are Segmented Based On the Market Capitalization of Cryptocurrencies (Bitcoin, Ethereum, Ripple, Bitcoin Cash, Cardano, and Others) and Cryptocurrency Adoption by Geography (Middle East & Africa, Americas, Europe, Apac). The Report Offers Market Size and Forecast Values for the Cryptocurrency Market in USD Million for the Above Segments.
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A total of 12,750 news headlines are obtained in the period between October 2021 and November 2022 from CoinTelegraph, CryptoNews and CryptoPotato.
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This dataset contains historical price data for Bitcoin (BTC/USDT) from January 1, 2018, to the present. The data is sourced using the Binance API, providing granular candlestick data in four timeframes: - 15-minute (15M) - 1-hour (1H) - 4-hour (4H) - 1-day (1D)
This dataset includes the following fields for each timeframe: - Open time: The timestamp for when the interval began. - Open: The price of Bitcoin at the beginning of the interval. - High: The highest price during the interval. - Low: The lowest price during the interval. - Close: The price of Bitcoin at the end of the interval. - Volume: The trading volume during the interval. - Close time: The timestamp for when the interval closed. - Quote asset volume: The total quote asset volume traded during the interval. - Number of trades: The number of trades executed within the interval. - Taker buy base asset volume: The volume of the base asset bought by takers. - Taker buy quote asset volume: The volume of the quote asset spent by takers. - Ignore: A placeholder column from Binance API, not used in analysis.
Binance API: Used for retrieving 15-minute, 1-hour, 4-hour, and 1-day candlestick data from 2018 to the present.
This dataset is automatically updated every day using a custom Python program.
The source code for the update script is available on GitHub:
🔗 Bitcoin Dataset Kaggle Auto Updater
This dataset is provided under the CC0 Public Domain Dedication. It is free to use for any purpose, with no restrictions on usage or redistribution.
When you need to analyze crypto market history, batch processing often beats streaming APIs. That's why we built the Flat Files S3 API - giving analysts and researchers direct access to structured historical cryptocurrency data without the integration complexity of traditional APIs.
Pull comprehensive historical data across 800+ cryptocurrencies and their trading pairs, delivered in clean, ready-to-use CSV formats that drop straight into your analysis tools. Whether you're building backtest environments, training machine learning models, or running complex market studies, our flat file approach gives you the flexibility to work with massive datasets efficiently.
Why work with us?
Market Coverage & Data Types: - Comprehensive historical data since 2010 (for chosen assets) - Comprehensive order book snapshots and updates - Trade-by-trade data
Technical Excellence: - 99,9% uptime guarantee - Standardized data format across exchanges - Flexible Integration - Detailed documentation - Scalable Architecture
CoinAPI serves hundreds of institutions worldwide, from trading firms and hedge funds to research organizations and technology providers. Our S3 delivery method easily integrates with your existing workflows, offering familiar access patterns, reliable downloads, and straightforward automation for your data team. Our commitment to data quality and technical excellence, combined with accessible delivery options, makes us the trusted choice for institutions that demand both comprehensive historical data and real-time market intelligence
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Analysis of ‘Crypto Fear and Greed Index’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/adelsondias/crypto-fear-and-greed-index on 13 February 2022.
--- Dataset description provided by original source is as follows ---
Each day, the website https://alternative.me/crypto/fear-and-greed-index/ publishes this index based on analysis of emotions and sentiments from different sources crunched into one simple number: The Fear & Greed Index for Bitcoin and other large cryptocurrencies.
The crypto market behaviour is very emotional. People tend to get greedy when the market is rising which results in FOMO (Fear of missing out). Also, people often sell their coins in irrational reaction of seeing red numbers. With our Fear and Greed Index, we try to save you from your own emotional overreactions. There are two simple assumptions:
Therefore, we analyze the current sentiment of the Bitcoin market and crunch the numbers into a simple meter from 0 to 100. Zero means "Extreme Fear", while 100 means "Extreme Greed". See below for further information on our data sources.
We are gathering data from the five following sources. Each data point is valued the same as the day before in order to visualize a meaningful progress in sentiment change of the crypto market.
First of all, the current index is for bitcoin only (we offer separate indices for large alt coins soon), because a big part of it is the volatility of the coin price.
But let’s list all the different factors we’re including in the current index:
We’re measuring the current volatility and max. drawdowns of bitcoin and compare it with the corresponding average values of the last 30 days and 90 days. We argue that an unusual rise in volatility is a sign of a fearful market.
Also, we’re measuring the current volume and market momentum (again in comparison with the last 30/90 day average values) and put those two values together. Generally, when we see high buying volumes in a positive market on a daily basis, we conclude that the market acts overly greedy / too bullish.
While our reddit sentiment analysis is still not in the live index (we’re still experimenting some market-related key words in the text processing algorithm), our twitter analysis is running. There, we gather and count posts on various hashtags for each coin (publicly, we show only those for Bitcoin) and check how fast and how many interactions they receive in certain time frames). A unusual high interaction rate results in a grown public interest in the coin and in our eyes, corresponds to a greedy market behaviour.
Together with strawpoll.com (disclaimer: we own this site, too), quite a large public polling platform, we’re conducting weekly crypto polls and ask people how they see the market. Usually, we’re seeing 2,000 - 3,000 votes on each poll, so we do get a picture of the sentiment of a group of crypto investors. We don’t give those results too much attention, but it was quite useful in the beginning of our studies. You can see some recent results here.
The dominance of a coin resembles the market cap share of the whole crypto market. Especially for Bitcoin, we think that a rise in Bitcoin dominance is caused by a fear of (and thus a reduction of) too speculative alt-coin investments, since Bitcoin is becoming more and more the safe haven of crypto. On the other side, when Bitcoin dominance shrinks, people are getting more greedy by investing in more risky alt-coins, dreaming of their chance in next big bull run. Anyhow, analyzing the dominance for a coin other than Bitcoin, you could argue the other way round, since more interest in an alt-coin may conclude a bullish/greedy behaviour for that specific coin.
We pull Google Trends data for various Bitcoin related search queries and crunch those numbers, especially the change of search volumes as well as recommended other currently popular searches. For example, if you check Google Trends for "Bitcoin", you can’t get much information from the search volume. But currently, you can see that there is currently a +1,550% rise of the query „bitcoin price manipulation“ in the box of related search queries (as of 05/29/2018). This is clearly a sign of fear in the market, and we use that for our index.
There's a story behind every dataset and here's your opportunity to share yours.
This dataset is produced and maintained by the administrators of https://alternative.me/crypto/fear-and-greed-index/.
This published version is an unofficial copy of their data, which can be also collected using their API (e.g., GET https://api.alternative.me/fng/?limit=10&format=csv&date_format=us).
--- Original source retains full ownership of the source dataset ---
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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.
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Bitcoin is the most well-known longest-running cryptocurrency, released initially as an open source in 2009 by Satoshi Nakamoto. Bitcoin is a decentralized medium of digital exchange, with transactions recorded and verified in a public distributed ledger (the blockchain) without the need for a record-keeping authority or central intermediary.
Transaction blocks contain an 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 the public adoption of bitcoin and continue to grow. Included here are historical bitcoin market data at 1-min intervals for select bitcoin exchanges where trading takes place. Happy (data) mining!
Features | Description |
---|---|
Date | Date of trading |
Currency | Contains Bitcoin name |
Closing Price | Contains closing exchange rate |
24 open | Contains opening exchange rate on day basis |
24 high | Contains information when the price was high on day basis |
24 low | Contains information when the price was low on day basis |
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Through Telegram API, the authors collected this database over four months ago. These data are Telegram's comments of over eight professional Telegram channels about cryptocurrencies from December 2023 to March 2024. The theory of Behavioral economics shows that the opinions of people, especially experts, can impact the stock market trend (here, cryptocurrencies). Existing databases often cover tweets or Telegram's comments on one or more cryptocurrencies. Also, in these databases, no attention is paid to the user's expertise, and most of the data is extracted using hashtags. Failure to pay attention to the user's expertise causes the irrelevant volume to increase and the neutral polarity considerably. This database has a main table with eight columns. The columns of the main table are explained in the attached document. Researchers can use this dataset in various machine learning tasks, such as sentiment analysis and deep transfer learning with sentiment analysis. Also, this data can be used to check the impact of influencers' opinions on the cryptocurrency market trend. The use of this database is allowed by mentioning the source. Furthermore, we have added Python code to extract Telegram's comments. We used the RoBERTa pre-trained deep neural network and BiGRU deep neural network with an attention layer-based HDRB model(https://ieeexplore.ieee.org/document/10292644) for sentiment analysis.
Bitcoin's blockchain size was close to reaching 5450 gigabytes in 2024, as the database saw exponential growth by nearly one gigabyte every few days. The Bitcoin blockchain contains a continuously growing and tamper-evident list of all Bitcoin transactions and records since its initial release in January 2009. Bitcoin has a set limit of 21 million coins, the last of which will be mined around 2140, according to a forecast made in 2017. Bitcoin mining: A somewhat uncharted world Despite interest in the topic, there are few accurate figures on how big Bitcoin mining is on a country-by-country basis. Bitcoin's design philosophy is at the heart of this. Created out of protest against governments and central banks, Bitcoin's blockchain effectively hides both the country of origin and the destination country within a (mining) transaction. Research involving IP addresses placed the United States as the world's most Bitcoin mining country in 2022 - but the source admits IP addresses can easily be manipulated using VPN. Note that mining figures are different from figures on Bitcoin trading: Africa and Latin America were more interested in buying and selling BTC than some of the world's developed economies. Bitcoin developments Bitcoin's trade volume slowed in the second quarter of 2023, after hitting a noticeable growth at the beginning of the year. The coin outperformed most of the market. Some attribute this to the announcement in June 203 that BlackRock filed for a Bitcoin ETF. This iShares Bitcoin Trust was to use Coinbase Custody as its custodian. Regulators in the United States had not yet approved any applications for spot ETFs on Bitcoin.
Our Market Data covers historical and real-time data. For CEXs, our data spans back to 2015, and for DEXs, we cover since the genesis trade. We cover every instrument on any exchange, so if it's traded, we cover it.
We understand you need to access the data you want, when and where you need it. With this in mind, we built our Market Data with several delivery options, including a robust streaming service offering the most advanced live data distribution in the cryptocurrency industry, as well as REST API, CSV via cloud services, and BigQuery.
Our Market Data empowers traders, analysts, and financial institutions with the insights needed to navigate the complex derivatives market effectively.
| Use Cases | Backtesting Hedging Trading Strategies Risk Management Regulatory Compliance
| Why work with us? |
A proven enterprise-grade solution We prioritize the needs of enterprises in our product development, ensuring our solutions meet the requirements of larger organizations seeking best-in-class crypto data.
A UI-free approach to crypto data We recognize the importance of flexibility when it comes to crypto data, and so we offer you complete freedom by taking a UI-free approach to data delivery. This gives you total control over how you use and interpret the data, reducing friction and streamlining workflows.
Flexible to meet your needs Flexibility lies at the heart of our product and is fundamental to how crypto data can deliver value across industries and use cases. Living this philosophy, we’re always building custom options that can help you achieve your specific objectives. Whether it’s tailoring a package to meet your requirements, or adapting infrastructure to support your use case, our data and product teams are on-hand to help you find the best way to achieve your priority outcomes.
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This dataset is about cryptos per hour, has 169 rows. and is filtered where the crypto is Bitcoin. It features 3 columns: crypto, datetime, and highest price. The preview is ordered by datetime (descending).
The dataset of this paper is collected based on Google, Blockchain, and the Bitcoin market. Generally, there is a total of 26 features, however, a feature whose correlation rate is lower than 0.3 between the variations of price and the variations of feature has been eliminated. Hence, a total of 21 practical features including Market capitalization, Trade-volume, Transaction-fees USD, Average confirmation time, Difficulty, High price, Low price, Total hash rate, Block-size, Miners-revenue, N-transactions-total, Google searches, Open price, N-payments-per Block, Total circulating Bitcoin, Cost-per-transaction percent, Fees-USD-per transaction, N-unique-addresses, N-transactions-per block, and Output-volume have been selected. In addition to the values of these features, for each feature, a new one is created that includes the difference between the previous day and the day before the previous day as a supportive feature. From the point of view of the number and history of the dataset used, a total of 1275 training data were used in the proposed model to extract patterns of Bitcoin price and they were collected from 12 Nov 2018 to 4 Jun 2021.
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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
Economic
Bitcoin,BTC,#btc,Cryptocurrency,Crypto
2808000
$149.00
How many cryptocurrencies are there? In short, there were over 9,000 as of 2023, although there were many more digital coins in the early months of 2022. Note, however, that a large portion of cryptocurrencies might not be that significant. There are other estimates of roughly 20,000 cryptocurrencies existing, but most of these are either inactive or discontinued. Due to how open the creation process of a cryptocurrency is, it is relatively easy to make one. Indeed, the top 20 cryptocurrencies make up nearly 90 percent of the total market. Why are there thousands of cryptocurrencies? Any private individual or company that knows how to write a program on a blockchain can technically create a cryptocurrency. That blockchain can be an existing one. Ethereum and Binance Smart Chain are popular blockchain platforms for such ends, including smart contracts within Decentralized Finance (DeFi). The ease of crypto creation allows some individuals to find solutions to real-world payment problems while others hope to make a quick profit. This explains why some crypto lack utility. Meme coins such as Dogecoin - named after a Japanese dog species - are an infamous example, with Dogecoin's creator coming out and stating the coin started as a joke. The many different types of cryptocurrency Meme coins are but one group of cryptocurrencies. Other types include altcoins, utility tokens, governance tokens, and stablecoins. Altcoins are often measured against Bitcoin, as this refers to all crypto that followed after Bitcoin - the first digital currency ever created. Utility tokens and governance tokens are somewhat connected to NFTs and the metaverse. A specific example is the MANA cryptocurrency, which allows real estate purchases in the Decentraland metaverse. Stablecoins refer to the likes of Tether, which are pegged to a real-world asset like the U.S. dollar. Such coins are meant to be less volatile than regular cryptocurrency.
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Analysis of ‘Crypto-data-part1’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/tusharsarkar/cryptodatapart1 on 28 January 2022.
--- Dataset description provided by original source is as follows ---
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.
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
--- Original source retains full ownership of the source dataset ---
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CryptoSentiment is a dataset, which contains sentiment information about cryptocurrency assets, gathered by various online sources, and analyzed by FinBERT sentiment extractor. More specifically, we provide a publicly available dataset containing fine-grained sentiment analysis data (minute-basis) about cryptocurrency market collected by different online sources. CryptoSentiment dataset includes 235,907 sentiment scores for 14 different cryptocurrencies gathered from various online sources such as news articles and social media.