Context

This minute by minute historical dataset of bitcoin prices offers a wealth of information for data scientists and analysts. In addition to the OHLC prices for each minute, this dataset also includes the volume of bitcoin traded during that time period. This granular data, going back to 2015, allows for in-depth analysis of the market fluctuations and trends of the world's most popular cryptocurrency.

With this dataset, researchers can study the underlying mechanisms of the bitcoin network, traders can gain a better understanding of market movements, and investors can make more informed decisions about their investments. The open, high, low, and close prices, as well as the volume data, provide a wealth of information for analyzing the market and identifying potential opportunities.

Whether you're looking to gain a competitive edge as a trader, conduct research on the bitcoin market, or simply want to learn more about the world of cryptocurrency, this dataset is a valuable resource. With its rich and detailed data, you'll be able to dive deep into the world of bitcoin and uncover insights that can help you make better decisions.

Content

• Timestamp: This is the UNIX timestamp or the "Epoch Time", number of seconds elapsed since 00:00:00 UTC on 1 January 1970.
• Date: Date and time of price recording.
• Open - This is the opening price of the time period (in US Dollars).
• High - This is the highest price of the time period (in US Dollars).
• Low - This is the lowest price of the time period (in US Dollars).
• Close - This is the closing price of the time period (in US Dollars).
• Volume BTC - This is the volume of ₿ transacted in the time interval.
• Volume USD - This is the volume of $ transacted in the time interval.

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

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.

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

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

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.

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.

BTC Bull Token price history tracking allows crypto investors to easily monitor the performance of their investment. You can conveniently track the opening value, high, and close for BTC Bull Token over time, as well as the trade volume. Additionally, you can instantly view the daily change as a percentage, making it effortless to identify days with significant fluctuations. According to our BTC Bull Token price history data, its value soared to an unprecedented peak in 2025-10-03, surpassing -- USD. On the other hand, the lowest point in BTC Bull Token's price trajectory, commonly referred to as the "BTC Bull Token all-time low", occurred on 2025-10-03. If one had purchased BTC Bull Token during that time, they would currently enjoy a remarkable profit of 0%. By design, 100,000,000 BTC Bull Token will be created. As of now, the circulating supply of BTC Bull Token is approximately 100,000,000. All the prices listed on this page are obtained from Bitget, a reliable source. It is crucial to rely on a single source to check your investments, as values may vary among different sellers. Our historical BTC Bull Token price dataset includes data at intervals of 1 minute, 1 day, 1 week, and 1 month (open/high/low/close/volume). These datasets have undergone rigorous testing to ensure consistency, completeness, and accuracy. They are specifically designed for trade simulation and backtesting purposes, readily available for free download, and updated in real-time.

About this dataset As cryptocurrency markets have gained prominence, individuals and organizations have shown an increased fascination with crafting automated trading strategies. The creation of algorithmic trading approaches, though, necessitates rigorous backtesting to ascertain their profitability. Consequently, the cornerstone of any triumphant algorithmic trading strategy lies in the availability of meticulously detailed historical trading data. This dataset will provide you a deeper understanding of working with this type of financial security, it provides you with open, high, low, close (OHLC) information, recorded at 1-hour intervals (not very high-velocity data), encompassing a multitude of cryptocurrency pairs. This data resource is invaluable for those seeking to devise and refine automated trading systems, data analysis, or predictions.

Content This dataset contains the historical trading data (OHLC) of 14 crypto securities at 1 1-hour resolution. The source of this data is Coindesk. The data in the CSV files is refined and cleaned for easier interpretation.

The data is free to use.

Context

Blockchain technology, first implemented by Satoshi Nakamoto in 2009 as a core component of Bitcoin, is a distributed, public ledger recording transactions. Its usage allows secure peer-to-peer communication by linking blocks containing hash pointers to a previous block, a timestamp, and transaction data. Bitcoin is a decentralized digital currency (cryptocurrency) which leverages the Blockchain to store transactions in a distributed manner in order to mitigate against flaws in the financial industry.

Nearly ten years after its inception, Bitcoin and other cryptocurrencies experienced an explosion in popular awareness. The value of Bitcoin, on the other hand, has experienced more volatility. Meanwhile, as use cases of Bitcoin and Blockchain grow, mature, and expand, hype and controversy have swirled.

Content

In this dataset, you will have access to information about blockchain blocks and transactions. All historical data are in the bigquery-public-data:crypto_bitcoin dataset. It’s updated it every 10 minutes. The data can be joined with historical prices in kernels. See available similar datasets here: https://www.kaggle.com/datasets?search=bitcoin.

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_bitcoin.[TABLENAME]. Fork this kernel to get started.

Method & Acknowledgements

Allen Day (Twitter | Medium), Google Cloud Developer Advocate & Colin Bookman, Google Cloud Customer Engineer retrieve data from the Bitcoin network using a custom client available on GitHub that they built with the bitcoinj Java library. Historical data from the origin block to 2018-01-31 were loaded in bulk to two BigQuery tables, blocks_raw and transactions. These tables contain fresh data, as they are now appended when new blocks are broadcast to the Bitcoin network. For additional information visit the Google Cloud Big Data and Machine Learning Blog post "Bitcoin in BigQuery: Blockchain analytics on public data".

Photo by Andre Francois on Unsplash.

Inspiration

• How many bitcoins are sent each day?
• How many addresses receive bitcoin each day?
• Compare transaction volume to historical prices by joining with other available data sources

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

This dataset contains historical Bitcoin (BTC/USDT) price data from Binance exchange with the following specifications:

Timezone Information: - All timestamps are in UTC (Coordinated Universal Time) - Open time format: YYYY-MM-DD HH:MM:SS.ffffff UTC - Close time format: YYYY-MM-DD HH:MM:SS.ffffff UTC

Daily Timeframe Specific: - Open time: Always shows 00:00:00.000000 UTC (start of day) - Close time: Always shows 23:59:59.999000 UTC (end of day)

Timeframes Available: - 15-minute intervals (15m) - 1-hour intervals (1h) - 4-hour intervals (4h) - 1-day intervals (1d)

Data Columns: - Open time: Opening timestamp in UTC - Open: Opening price - High: Highest price during period - Low: Lowest price during period - Close: Closing price - Volume: Trading volume - Close time: Closing timestamp in UTC - Quote asset volume: Volume in quote asset (USDT) - Number of trades: Number of trades during period - Taker buy base asset volume: Volume of taker buy orders - Taker buy quote asset volume: Volume of taker buy orders in quote asset - Ignore: Unused field

Data is automatically updated and maintained through automated scripts.

Delving into the realm of Bitcoin inputs, this dataset provides a broad and detailed view. Highlighting the intricate workings of the blockchain system, it stands as a continuously updated, invaluable asset in the ever-changing landscape of blockchain. This resource is a wellspring of information, suitable for various users. Whether you're a financial professional examining input dynamics, a researcher navigating the subtleties of input structures, or a blockchain enthusiast keen on understanding this technology's core components, this dataset is tailored for your exploration.

For any additional information or questions about this input dataset, please reach out to us at info@blockchair.com. Our devoted team is on standby to assist, ensuring you gain the utmost value from the data presented.

Research on Bitcoin's Potential Future Valuation

Title: The Future of Bitcoin: A Quadrillion-Dollar Industry?

This research paper investigates the potential for Bitcoin (BTC) to reach a quadrillion-dollar market cap, with individual BTC prices surpassing $48,000,000. The study examines historical data, market trends, technological advancements, macroeconomic influences, and expert opinions to understand the factors driving such projections.

Key highlights include:

1. Historical Data and Market Trends:

   • Bitcoin's price evolution from $0.0041 in 2009 to $75,830 in 2024, marked by significant events such as the Genesis block, Silk Road shutdown, and Tesla's investment.
   • The dataset provides annual high and low prices, alongside major milestones.

2. Technological Advancements:

   • Developments like the Lightning Network and Taproot upgrade enhance transaction speed and efficiency, boosting adoption.

3. Macroeconomic Influences:

   • Bitcoin's role as a hedge against inflation and its fixed supply contrast with fiat currencies.
   • Growth predictions based on M0, M1, and M2 money supply comparisons.

4. Expert Opinions and Future Projections:

   • Insights from Marion Laboure of Deutsche Bank and predictions from CoinCheckup indicate a bullish trend, with potential prices reaching $173,818.51 in a year.

Conclusion: The combination of technological progress, economic factors, and growing adoption points to significant growth potential for Bitcoin. This research offers valuable insights for investors and policymakers.

References:

• Investopedia, TradingView, CoinCheckup, Deutsche Bank Research, 99bitcoins, Bitcoin Magazine, Forbes India.

Data Pre-Processing Notebook:**

• Notebook: Pre-Prep & Technical Indicators Bitcoin Market Data

Main Datasets:

• power_data.csv: ready to load, already pre-processed with all features, technical indicators.
• Shape: 1,997,210 rows, 27 columns
• Misc: 774MB
• Time Period: From 2020-01-01 00:01:00 to 2023-10-22 23:59:00
• Misc: If you want raw data files, please see version 3

Description:

This dataset provides a view of Bitcoin (BTC) market data by the minute, spanning from 2020 to the current date of October 24, 2023. It provided a wealth of valuable information (pure gold) for those interested in analyzing and understanding the minute-by-minute dynamics of the BTC market. Suitable for Algorithmic Trading, Neural Network, Reinforcement Learning, Machine Learning, Statistical Analysis and any kind of predictive analysis.

Key Features:

• OHLCV Data: The dataset includes Open, High, Low, Close, and Volume (OHLCV) information, which are essential components for charting and analyzing price movements in the BTC market.
• Trade Count: The number of trades that occurred within each minute, offering insights into trading activity and market participation.
• Date Data: day (object) & hour (int) features

Technical Indicators:

• Multiple EMAs (Exponential Moving Averages): These moving averages provide a dynamic view of the market by giving more weight to recent data points, making them particularly responsive to current price movements.
• WMA (Weighted Moving Average): A 14-period WMA offers a moving average that assigns varying weights to each data point in the series, thus providing a different perspective on price trends.
• MACD (Moving Average Convergence Divergence): MACD, Signal Line, and Histogram are included, offering a comprehensive view of this trend-following momentum indicator, which highlights the relationship between two moving averages.
• ATR (Average True Range): ATR measures market volatility by calculating the average range between high and low prices, making it a valuable tool for assessing price volatility.
• HMA (Hull Moving Average): This weighted moving average is designed to reduce lag and increase responsiveness to price changes, allowing for more timely analysis.
• KAMA (Kaufman's Adaptive Moving Average): KAMA is an adaptive moving average that adjusts its speed based on market conditions, providing a more dynamic view of price trends.
• CMO (Chande Momentum Oscillator): The Chande Momentum Oscillator measures price changes relative to the total range of prices over a specified period, facilitating insights into market momentum.
• Z-Score: The Z-Score measures how far a data point is from the mean in terms of standard deviations, helping to identify extreme deviations from the norm.
• QStick: QStick measures momentum based on the difference between the opening and closing prices, allowing for a deeper understanding of price movements within each minute.

This dataset dives deep into the intricacies of Bitcoin Cash blocks, presenting a comprehensive and holistic perspective. It meticulously captures unique attributes inherent to block datasets, such as block size, the number of transactions, and miner rewards, offering a window into the complex mechanics of the blockchain ecosystem. Updated in real-time, this dataset stands as a testament to the ever-evolving world of blockchain, making it an invaluable resource for a broad spectrum of users. Whether you're a financial expert analyzing block dynamics, a researcher delving into the subtleties of block configurations, or a blockchain aficionado eager to grasp the foundational elements, this dataset is designed with you in mind.

If you require further insights or have any inquiries regarding this dataset, please don't hesitate to contact us at info@blockchair.com. Our team is dedicated to assisting you and ensuring you maximize the value of the information provided.

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.

Context

With the rise of crypto currency markets the interest in creating automated trading strategies, or trading bots, has grown. Developing algorithmic trading strategies however requires intensive backtesting to ensure profitable performance. It follows that access to high resolution historical trading data is the foundation of every successful algorithmic trading strategy. This dataset therefore provides open, high, low, close (OHLC) data at 1 minute resolution of various crypto currency pairs for the development of automated trading systems.

Content

It is the data of last 8 years approx. of the most famous cryptocurrency "Bitcoin", having attributes such as date itself, it's opening bid price, high and low of the days, close price and the volume of trade.

Certain targets can be set while accessing the dataset dataset such as:

Q: Adding an attribute of "percent change" on each day (as compared to last day close price of-coarse) Q: Visualization of the BTC and its highest and lowest values across years Q: At what days of the week it shows uptrend & downtrend more often (if it shows any such specific trend at all) Q: When it showed dramatic bullish trend and the possible potential reason behind it? Q: (Most important) Possible estimation where it is headed for in 2022? What is the potential min and max values? (Do time-series forecasting)

Acknowledgement

Data has been obtained through the Bitfinex API

This dataset dives deep into the intricacies of Bitcoin blocks, presenting a comprehensive and holistic perspective. It meticulously captures unique attributes inherent to block datasets, such as block size, the number of transactions, and miner rewards, offering a window into the complex mechanics of the blockchain ecosystem. Updated in real-time, this dataset stands as a testament to the ever-evolving world of blockchain, making it an invaluable resource for a broad spectrum of users. Whether you're a financial expert analyzing block dynamics, a researcher delving into the subtleties of block configurations, or a blockchain aficionado eager to grasp the foundational elements, this dataset is designed with you in mind.

If you require further insights or have any inquiries regarding this dataset, please don't hesitate to contact us at info@blockchair.com. Our team is dedicated to assisting you and ensuring you maximize the value of the information provided.

Context

Bitcoin(₿) is a cryptocurrency invented in 2008 by an unknown person or group of people using the name Satoshi Nakamoto. The currency began use in 2009 when its implementation was released as open-source software.

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. Bitcoins are created as a reward for a process known as mining. They can be exchanged for other currencies, products, and services.

On 30 November 2020, bitcoin hit a new all-time high of $19,860 topping the previous high from December 2017. On 19 January 2021 Elon Musk placed #Bitcoin in his Twitter profile tweeting “In retrospect, it was inevitable”, which caused the price to briefly rise about $5000 in an hour to $37,299.

Content

The tweets have #Bitcoin and #btc hashtag. Collection star started on 6/2/2021, with an initial 1 lakh tweets, and will continue on a daily basis.

Information regarding the data

The data totally consists of 1 lakh+ records with 13 columns. The description of the features is given below | No |Columns | Descriptions | | -- | -- | -- | | 1 | user_name | The name of the user, as they’ve defined it. | | 2 | user_location | The user-defined location for this account’s profile. | | 3 | user_description | The user-defined UTF-8 string describing their account. | | 4 | user_created | Time and date, when the account was created. | | 5 | user_followers | The number of followers an account currently has. | | 6 | user_friends | The number of friends a account currently has. | | 7 | user_favourites | The number of favorites a account currently has | | 8 | user_verified | When true, indicates that the user has a verified account | | 9 | date | UTC time and date when the Tweet was created | | 10 | text | The actual UTF-8 text of the Tweet | | 11 | hashtags | All the other hashtags posted in the tweet along with #Bitcoin & #btc | | 12 | source | Utility used to post the Tweet, Tweets from the Twitter website have a source value - web | | 13 | is_retweet | Indicates whether this Tweet has been Retweeted by the authenticating user. |

Inspiration

The tweets were extracted using tweepy, Refer to this notebook for the complete extraction process https://www.kaggle.com/kaushiksuresh147/twitter-data-extraction-for-ipl2020

You can use this data to dive into the subjects that use this hashtag, look to the geographical distribution, evaluate sentiments, looks to trends.