9 datasets found
  1. BITCOIN Historical Datasets 2018-2025 Binance API

    • kaggle.com
    Updated May 11, 2025
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    Novandra Anugrah (2025). BITCOIN Historical Datasets 2018-2025 Binance API [Dataset]. https://www.kaggle.com/datasets/novandraanugrah/bitcoin-historical-datasets-2018-2024
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 11, 2025
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Novandra Anugrah
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Bitcoin Historical Data (2018-2024) - 15M, 1H, 4H, and 1D Timeframes

    Dataset Overview

    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.

    Data Sources

    Binance API: Used for retrieving 15-minute, 1-hour, 4-hour, and 1-day candlestick data from 2018 to the present.

    File Contents

    1. btc_15m_data_2018_to_present.csv: 15-minute interval data from 2018 to the present.
    2. btc_1h_data_2018_to_present.csv: 1-hour interval data from 2018 to the present.
    3. btc_4h_data_2018_to_present.csv: 4-hour interval data from 2018 to the present.
    4. btc_1d_data_2018_to_present.csv: 1-day interval data from 2018 to the present.

    Automated Daily Updates

    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

    Licensing

    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.

  2. Bitcoin (BTC) blockchain size as of May 13, 2025

    • statista.com
    • ai-chatbox.pro
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    Statista, Bitcoin (BTC) blockchain size as of May 13, 2025 [Dataset]. https://www.statista.com/statistics/647523/worldwide-bitcoin-blockchain-size/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    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.

  3. Bitcoin (BTC) daily network transaction history worldwide as of April 21,...

    • statista.com
    • ai-chatbox.pro
    Updated Jun 23, 2025
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    Statista (2025). Bitcoin (BTC) daily network transaction history worldwide as of April 21, 2025 [Dataset]. https://www.statista.com/statistics/730806/daily-number-of-bitcoin-transactions/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Bitcoin's transaction volume was at its highest in December 2023, when the network processed over ******* coins on the same day. Bitcoin generally has a higher transaction activity than other cryptocurrencies, except Ethereum. This cryptocurrency is often processed more than *********** times per day. Note that the transaction volume here refers to transactions registered within the Bitcoin blockchain. It should not be confused with Bitcoin's 24-hour trade volume, a metric associated with crypto exchanges. The more Bitcoin transactions, the more it is used in B2C payments? A Bitcoin transaction recorded in the blockchain can be any transaction, including B2C but also P2P. While it is possible to see in the blockchain which address sent Bitcoin to whom, details on who this person is and where they are from are typically missing. Bitcoin was designed to go against monetary authorities and prides itself on being anonymous. An important argument against Bitcoin replacing cash or cards in payments is that the cryptocurrency was not allowed for such a task: Bitcoin ranks among the slowest cryptocurrencies in terms of transaction speed. Are cryptocurrencies taking over payments? Cryptocurrency payments are set to grow at a CAGR of nearly ** percent between 2022 and 2029, although the market is relatively small. The forecast is according to a market estimate made in early 2023, based on various conditions and sources available at that time. Research across ** countries during the same time suggested that the market share of cryptocurrency in e-commerce transactions was "less than *** percent" in all surveyed countries, with predictions being this would not change in the future.

  4. Bitcoin (BTC) blockchain size as of June 29, 2025

    • statista.com
    Updated Mar 21, 2025
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    Raynor de Best (2025). Bitcoin (BTC) blockchain size as of June 29, 2025 [Dataset]. https://www.statista.com/study/24546/bitcoin/
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    Dataset updated
    Mar 21, 2025
    Dataset provided by
    Statistahttp://statista.com/
    Authors
    Raynor de Best
    Description

    Bitcoin's blockchain size was close to reaching 652.93 gigabytes in June 2025, 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 2023 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.

  5. Z

    Data from: A Dataset of Coordinated Cryptocurrency-Related Social Media...

    • data.niaid.nih.gov
    Updated Jul 12, 2024
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    Zilius, Karolis (2024). A Dataset of Coordinated Cryptocurrency-Related Social Media Campaigns [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_7539178
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    Dataset updated
    Jul 12, 2024
    Dataset provided by
    van Moorsel, Aad
    Zilius, Karolis
    Spiliotopoulos, Tasos
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Note: This version simply updates the dataset with a new Readme - Supplementary Material file.

    The paper describing this dataset can be cited as:

    Zilius, K., Spiliotopoulos, T., & van Moorsel, A. (2023). A Dataset of Coordinated Cryptocurrency-Related Social Media Campaigns. Proceedings of the International AAAI Conference on Web and Social Media, 17(1), 1112-1121. https://doi.org/10.1609/icwsm.v17i1.22219

    Abstract

    The rise in adoption of cryptoassets has brought many new and inexperienced investors in the cryptocurrency space. These investors can be disproportionally influenced by information they receive online, and particularly from social media. This paper presents a dataset of crypto-related bounty events and the users that participate in them. These events coordinate social media campaigns to create artificial "hype" around a crypto project in order to influence the price of its token. The dataset consists of information about 15.8K cross-media bounty events, 185K participants, 10M forum comments and 82M social media URLs collected from the Bounties(Altcoins) subforum of the BitcoinTalk online forum from May 2014 to December 2022. We describe the data collection and the data processing methods employed and we present a basic characterization of the dataset. Furthermore, we discuss potential research opportunities afforded by the dataset across many disciplines and we highlight potential novel insights into how the cryptocurrency industry operates and how it interacts with its audience.

  6. m

    Database of influencers' tweets in cryptocurrency (2021-2023).

    • data.mendeley.com
    • cryptodata.center
    Updated Aug 22, 2023
    + more versions
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    kia jahanbin (2023). Database of influencers' tweets in cryptocurrency (2021-2023). [Dataset]. http://doi.org/10.17632/8fbdhh72gs.5
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    Dataset updated
    Aug 22, 2023
    Authors
    kia jahanbin
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Authors, through Twitter API, collected this database over eight months. These data are tweets of over 50 experts regarding market analysis of 40 cryptocurrencies. These experts are known as influencers on social networks such as Twitter. 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 related to 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 to increase considerably. This database has a main table named "Tweets1" with 11 columns and 40 tables to separate comments related to each cryptocurrency. The columns of the main table and the cryptocurrency tables 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. Also, in this version, we have added the excel version of the database and Python code to extract the names of influencers and tweets. in Version(3): In the new version, three datasets related to historical prices and sentiments related to Bitcoin, Ethereum, and Binance have been added as Excel files from January 1, 2023, to June 12, 2023. Also, two datasets of 52 influential tweets in cryptocurrencies have been published, along with the score and polarity of sentiments regarding more than 300 cryptocurrencies from February 2021 to June 2023. Also, two Python codes related to the sentiment analysis algorithm of tweets with Python have been published. This algorithm combines RoBERTa pre-trained deep neural network and BiGRU deep neural network with an attention layer (see code Preprocessing_and_sentiment_analysis with python).

  7. Crypto Price Monitoring Dataset for On-chain Derivatives Research

    • zenodo.org
    csv
    Updated Mar 19, 2023
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    Ivan Vakhmyanin; Yana Volkovich; Ivan Vakhmyanin; Yana Volkovich (2023). Crypto Price Monitoring Dataset for On-chain Derivatives Research [Dataset]. http://doi.org/10.5281/zenodo.7749133
    Explore at:
    csvAvailable download formats
    Dataset updated
    Mar 19, 2023
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Ivan Vakhmyanin; Yana Volkovich; Ivan Vakhmyanin; Yana Volkovich
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    # Crypto Price Monitoring Repository

    This repository contains two CSV data files that were created to support the research titled "Price Arbitrage for DeFi Derivatives." This research is to be presented at the IEEE International Conference on Blockchain and Cryptocurrencies, taking place on 5th May 2023 in Dubai, UAE. The data files include monitoring prices for various crypto assets from several sources. The data files are structured with five columns, providing information about the symbol, unified symbol, time, price, and source of the price.

    ## Data Files

    There are two CSV data files in this repository (one for each date):

    1. `Pricemon_results_2023_01_13.csv`
    2. `Pricemon_results_2023_01_14.csv`

    ## Data Format

    Both data files have the same format and structure, with the following five columns:

    1. `symbol`: The trading symbol for the crypto asset (e.g., BTC, ETH).
    2. `unified_symbol`: A standardized symbol used across different platforms.
    3. `time`: Timestamp for when the price data was recorded (in UTC format).
    4. `price`: The price of the crypto asset at the given time (in USD).
    5. `source`: The name of the price source for the data.

    ## Price Sources

    The `source` column in the data files refers to the provider of the price data for each record. The sources include:

    - `chainlink`: Chainlink Price Oracle
    - `mycellium`: Built-in oracle of the Mycellium platform
    - `bitfinex`: Bitfinex cryptocurrency exchange
    - `ftx`: FTX cryptocurrency exchange
    - `binance`: Binance cryptocurrency exchange

    ## Usage

    You can use these data files for various purposes, such as analyzing price discrepancies across different sources, identifying trends, or developing trading algorithms. To use the data, simply import the CSV files into your preferred data processing or analysis tool.

    ### Example

    Here's an example of how you can read and display the data using Python and the pandas library:

    import pandas as pd

    # Read the data from CSV file
    data = pd.read_csv('Pricemon_results_2023_01_13.csv')

    # Display the first 5 rows of the data
    print(data.head())`

    ## Acknowledgements

    These datasets were recorded and supported by Datamint company (value-added on-chain data provider) and its team.


    ## Contributing

    If you have any suggestions or find any issues with the data, please feel free to contact authors.

  8. Annual cryptocurrency adoption in 56 different countries worldwide 2019-2025...

    • statista.com
    • ai-chatbox.pro
    Updated May 27, 2025
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    Statista (2025). Annual cryptocurrency adoption in 56 different countries worldwide 2019-2025 [Dataset]. https://www.statista.com/statistics/1202468/global-cryptocurrency-ownership/
    Explore at:
    Dataset updated
    May 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Consumers from countries in Africa, Asia, and South America were most likely to be an owner of cryptocurrencies, such as Bitcoin, in 2025. This conclusion can be reached after combining ** different surveys from the Statista's Consumer Insights over the course of that year. Nearly one out of three respondents to Statista's survey in Nigeria, for instance, mentioned they either owned or use a digital coin, rather than *** out of 100 respondents in the United States. This is a significant change from a list that looks at the Bitcoin (BTC) trading volume in ** countries: There, the United States and Russia were said to have traded the highest amounts of this particular virtual coin. Nevertheless, African and Latin American countries are noticeable entries in that list too. Daily use, or an investment tool? The survey asked whether consumers either owned or used cryptocurrencies but does not specify their exact use or purpose. Some countries, however, are more likely to use digital currencies on a day-to-day basis. Nigeria increasingly uses mobile money operations to either pay in stores or to send money to family and friends. Polish consumers could buy several types of products with a cryptocurrency in 2019. Opposed to this is the country of Vietnam: Here, the use of Bitcoin and other cryptocurrencies as a payment method is forbidden. Owning some form of cryptocurrency in Vietnam as an investment is allowed, however. Which countries are more likely to invest in cryptocurrencies? Professional investors looking for a cryptocurrency-themed ETF were more often found in Europe than in the United or China, according to a survey in early 2020. Most of the largest crypto hedge fund managers with a location in Europe in 2020, were either from the United Kingdom or Switzerland - the country with the highest cryptocurrency adoption rate in Europe according to Statista's Global Consumer Survey. Whether this had changed by 2025 was not yet clear.

  9. Data from: Horizon of cryptocurrency before vs during COVID-19 - Dataset -...

    • cryptodata.center
    Updated Dec 4, 2024
    + more versions
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    cryptodata.center (2024). Data from: Horizon of cryptocurrency before vs during COVID-19 - Dataset - CryptoData Hub [Dataset]. https://cryptodata.center/dataset/data-from-horizon-of-cryptocurrency-before-vs-during-covid-19
    Explore at:
    Dataset updated
    Dec 4, 2024
    Dataset provided by
    CryptoDATA
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    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)

  10. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Novandra Anugrah (2025). BITCOIN Historical Datasets 2018-2025 Binance API [Dataset]. https://www.kaggle.com/datasets/novandraanugrah/bitcoin-historical-datasets-2018-2024
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BITCOIN Historical Datasets 2018-2025 Binance API

BTCUSDT spot crypto Binance (Daily, 4h, 1h, 15m) update to current day

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
May 11, 2025
Dataset provided by
Kagglehttp://kaggle.com/
Authors
Novandra Anugrah
License

https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

Description

Bitcoin Historical Data (2018-2024) - 15M, 1H, 4H, and 1D Timeframes

Dataset Overview

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.

Data Sources

Binance API: Used for retrieving 15-minute, 1-hour, 4-hour, and 1-day candlestick data from 2018 to the present.

File Contents

  1. btc_15m_data_2018_to_present.csv: 15-minute interval data from 2018 to the present.
  2. btc_1h_data_2018_to_present.csv: 1-hour interval data from 2018 to the present.
  3. btc_4h_data_2018_to_present.csv: 4-hour interval data from 2018 to the present.
  4. btc_1d_data_2018_to_present.csv: 1-day interval data from 2018 to the present.

Automated Daily Updates

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

Licensing

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.

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