Cryptocurrency Transaction Flow Dataset

Columns

• Transaction_ID: A unique identifier for each cryptocurrency transaction [2].
• Sender_Address: The blockchain address of the sender initiating the transaction [2].
• Receiver_Address: The blockchain address of the recipient receiving the transaction [2].
• Amount: The total amount of cryptocurrency transferred in the transaction (in either BTC or ETH) [2, 3]. This is a Float type, with values ranging from 0.01 to 15, a mean of 7.52, and a standard deviation of 4.32 [4].
• Transaction_Fee: The transaction fee paid to process the transaction [3]. This is a Float type, with all recorded values being 0 in the provided sample [4, 5].
• Timestamp: The date and time when the transaction was processed, in ISO 8601 format [3]. Dates in the dataset range from 3rd March 2025 to 11th May 2025 [6].
• Block_ID: The unique identifier for the block that the transaction was included in [3].
• Mining_Pool: The name of the mining pool that confirmed the transaction [7]. The most common pools are Ethermine (60%) and Poolin (10%), with other pools making up 30% [8].
• Currency: The cryptocurrency type involved in the transaction (either BTC or ETH) [7]. Both BTC and ETH account for 50% of the transactions [8].
• Transaction_Type: The type of the transaction, which is typically "Transfer" for regular cryptocurrency transfers [7]. All entries in the dataset are "Transfer" [8].
• Transaction_Status: The current status of the transaction, such as "Confirmed" [7, 9]. All entries in the dataset are "Confirmed" [10].
• Gas_Price_Gwei: The gas price for Ethereum transactions, measured in Gwei (applicable only to ETH transactions) [9]. This is an Integer type, with values ranging from 10 to 50, a mean of 27.1, and a standard deviation of 13. There are 25,000 valid entries, and 25,000 missing entries (50%) as it only applies to Ethereum transactions [10].

Distribution

Usage

• Market Trend Analysis: Analysing transaction patterns to identify market trends and behaviours, and tracking spikes or drops in transaction volumes to correlate with market events or price movements [9].
• Blockchain Dynamics: Studying how mining pools and transaction fees interact with blockchain dynamics, and investigating how different mining pools impact transaction confirmation times and fees across Bitcoin and Ethereum networks [14].
• Trading Behaviour: Investigating the behaviour of users sending or receiving cryptocurrency, and identifying patterns such as frequent senders/receivers, average transaction amounts, and transaction frequency [14].
• Fee and Gas Price Optimisation: Exploring transaction fees and gas price fluctuations across different mining pools and blockchains, and examining how Ethereum’s gas prices and Bitcoin’s transaction fees fluctuate over time and affect user behaviour [14].

Coverage

License

Who Can Use It

• Data Scientists and Analysts: For conducting market trend analysis, blockchain research, and studying user behaviour in cryptocurrency markets [9, 14].
• Financial Researchers: To understand the dynamics of transaction fees and gas prices and their impact on market efficiency [14].
• Blockchain Developers: To gain insights into mining pool performance and transaction processing across different networks [14].
• Investors and Traders: To identify patterns in trading activity and correlate them with market movements [9].

Dataset Name Suggestions

• Bitcoin & Ethereum Transaction Analytics
• Crypto Transaction Data 2025
• BTC ETH Blockchain Insights
• Cryptocurrency Transaction Flow Dataset

Attributes