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Major Crypto and Currency Pair Daily Data

Crypto & Blockchain Transactions

Tags and Keywords

Crypto

Finance

Blockchain

Currencies

Investing

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Major Crypto and Currency Pair Daily Data Dataset on Opendatabay data marketplace

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About

This dataset provides historical daily price data for twelve prominent cryptocurrencies and two well-known currency pairs, covering the period from 2018 to 2023. It offers insights into the dynamic world of digital assets and foreign exchange markets. Cryptocurrencies are decentralised digital forms of money built on blockchain technology, employing encryption to secure and authenticate transactions. Unlike traditional fiat currencies, they are not typically issued by a central authority. The dataset also includes information on currency pairs, which illustrate the value of one currency against another, identified by their ISO codes. This collection is ideal for financial analysis, market trend observation, and research into the evolution of digital and traditional currency valuations.

Columns

  • Type: Indicates the specific currency or currency pair (e.g., Tether USD, Bitcoin USD, EUR/USD).
  • Date: The chronological date of the recorded price, ranging from 1 January 2018 to 31 December 2022.
  • Open: The opening price of the currency or currency pair on the given date.
  • High: The highest price reached by the currency or currency pair on the given date.
  • Low: The lowest price observed for the currency or currency pair on the given date.
  • Close: The closing price of the currency or currency pair on the given date.
  • Adj Close: The closing price, adjusted to account for any corporate actions that may have affected the stock's value.
  • Volume: The total trading volume of the currency or currency pair on the given date.

Distribution

The dataset is provided as a CSV file, named "12 Well-known Crypto(currency) 2018-2023.csv", with a file size of 1.57 MB. It contains 8 columns and approximately 19,800 records. No specific row or record count is given for the full dataset, but valid entries for each column are consistently around 19.8 thousand.

Usage

This dataset is well-suited for a variety of applications, including:
  • Financial analysis and modelling: Examining historical price movements and volatility.
  • Investing research: Identifying trends and patterns in cryptocurrency and foreign exchange markets.
  • Exploratory Data Analysis (EDA): Gaining initial insights into market behaviour.
  • Time Series Analysis: Developing predictive models for future price movements.
  • Educational purposes: Studying the fundamentals of digital assets and currency trading.

Coverage

The dataset spans a time range from 2018 to 2023, with specific daily data recorded between 1 January 2018 and 31 December 2022. It covers the performance of twelve major cryptocurrencies, including Tether, Bitcoin, Ethereum, TRON, BNB, XRP, Cardano, Dogecoin, Litecoin, and Polkadot. Additionally, it includes data for two prominent currency pairs, EUR/USD and GBP/USD. The data represents global financial markets, focusing on widely traded digital assets and international currency exchanges.

License

CC0: Public Domain

Who Can Use It

This dataset is invaluable for:
  • Financial Analysts: To conduct market research and trend analysis.
  • Data Scientists: For building and testing predictive models for asset prices.
  • Investors: To inform trading strategies and portfolio management.
  • Academics and Students: For research in economics, finance, and blockchain technology.
  • Researchers: Studying the dynamics of digital currencies and foreign exchange.

Dataset Name Suggestions

  • Historical Cryptocurrency & Forex Rates (2018-2023)
  • Major Crypto and Currency Pair Daily Data
  • Global Digital Assets & FX Market History
  • Cryptocurrency and Fiat Currency Exchange Data
  • Financial Market Data: Crypto & Forex OHLCV

Attributes

Listing Stats

VIEWS

0

DOWNLOADS

0

LISTED

30/08/2025

REGION

GLOBAL

Universal Data Quality Score Logo UDQSQUALITY

5 / 5

VERSION

1.0

Free

Download Dataset in CSV Format