Omarrran/50k_Cryptocurrency_Transaction_Dataset_by_HNM

Cryptocurrency Transaction Datasets (Dataset: 5 cryptocurrencies × 10,000 transactions each = 50,000 total transactions)

This dataset collection comprises transaction data for five major cryptocurrencies: Ethereum Classic (ETC), Bitcoin (BTC), Dogecoin (DOGE), Bitcoin Cash (BCH), and Dash (DASH). Each dataset contains 10,000 transactions, offering a snapshot of network activity. A key distinction among these cryptocurrencies lies in their underlying transaction model: ETC operates on an Account-based model, where transactions transfer value between accounts, while BTC, DOGE, BCH, and DASH utilize the Unspent Transaction Output (UTXO) model, where transactions consume unspent outputs and create new ones. This fundamental difference is reflected in the schema and metrics available for each chain, providing a rich resource for comparative analysis of blockchain transaction dynamics.

Column Descriptions

ETC Schema

Column Name	Description
hash	The unique identifier (hash) of the transaction.
block_number	The block number in which the transaction was included.
block_timestamp	The timestamp of the block in which the transaction was included.
from_address	The sender's address of the transaction.
to_address	The recipient's address of the transaction.
value_etc	The amount of Ethereum Classic (ETC) transferred in the transaction.
gas	The amount of gas used by the transaction.
gas_price_gwei	The price of gas in GWEI paid for the transaction.
receipt_status	The status of the transaction receipt (1 for success, 0 for failure).

BTC Schema

Column Name	Description
hash	The unique identifier (hash) of the transaction.
block_number	The block number in which the transaction was included.
block_timestamp	The timestamp of the block in which the transaction was included.
input_btc	The total input value in BTC for the transaction. Note: This can be null for coinbase transactions or if specific inputs are not tracked.
output_btc	The total output value in BTC for the transaction. Note: This can be null if no outputs or specific outputs are not tracked.
fee_btc	The transaction fee in BTC (difference between total inputs and total outputs).
input_count	The number of inputs in the transaction.
output_count	The number of outputs in the transaction.
is_coinbase	Boolean indicating if the transaction is a coinbase transaction (block reward).

DOGE Schema

Column Name	Description
hash	The unique identifier (hash) of the transaction.
block_number	The block number in which the transaction was included.
block_timestamp	The timestamp of the block in which the transaction was included.
input_doge	The total input value in DOGE for the transaction. Note: This can be null for coinbase transactions or if specific inputs are not tracked.
output_doge	The total output value in DOGE for the transaction. Note: This can be null if no outputs or specific outputs are not tracked.
fee_doge	The transaction fee in DOGE (difference between total inputs and total outputs).
input_count	The number of inputs in the transaction.
output_count	The number of outputs in the transaction.
is_coinbase	Boolean indicating if the transaction is a coinbase transaction (block reward).

BCH Schema

Column Name	Description
hash	The unique identifier (hash) of the transaction.
block_number	The block number in which the transaction was included.
block_timestamp	The timestamp of the block in which the transaction was included.
input_bch	The total input value in BCH for the transaction. Note: This can be null for coinbase transactions or if specific inputs are not tracked.
output_bch	The total output value in BCH for the transaction. Note: This can be null if no outputs or specific outputs are not tracked.
fee_bch	The transaction fee in BCH (difference between total inputs and total outputs).
input_count	The number of inputs in the transaction.
output_count	The number of outputs in the transaction.
is_coinbase	Boolean indicating if the transaction is a coinbase transaction (block reward).

DASH Schema

Column Name	Description
hash	The unique identifier (hash) of the transaction.
block_number	The block number in which the transaction was included.
block_timestamp	The timestamp of the block in which the transaction was included.
input_dash	The total input value in DASH for the transaction. Note: This can be null for coinbase transactions or if specific inputs are not tracked.
output_dash	The total output value in DASH for the transaction. Note: This can be null if no outputs or specific outputs are not tracked.
fee_dash	The transaction fee in DASH (difference between total inputs and total outputs).
input_count	The number of inputs in the transaction.
output_count	The number of outputs in the transaction.
is_coinbase	Boolean indicating if the transaction is a coinbase transaction (block reward).

Key Statistics

ETC Statistics

• Shape: 10000 rows, 9 columns

• Missing Values: None

• Data Types:

  • hash: object
  • block_number: int64
  • block_timestamp: datetime64[ns, UTC]
  • from_address: object
  • to_address: object
  • value_etc: float64
  • gas: int64
  • gas_price_gwei: float64
  • receipt_status: int64

• Descriptive Statistics:

	block_number	value_etc	gas	gas_price_gwei	receipt_status
count	10000	10000	10000	10000	10000
mean	1.16598e+07	75.7417	51210.1	6.20064	0.9993
std	811.228	1358.07	222979	41.5924	0.0264496
min	1.16583e+07	0	21000	1	0
25%	1.1659e+07	0.121622	21000	1	1
50%	1.16598e+07	0.364524	50000	1	1
75%	1.16605e+07	1.01534	50000	7	1
max	1.16612e+07	91500	8e+06	4000	1

• Value (value_etc): Ranges from 0.00 to 91499.99 ETC, with an average of 75.74 ETC, indicating a wide range of transaction values.
• Gas Price (gas_price_gwei): Shows a significant spread from 1.00 to 4000.00 GWEI, with a mean of 6.20 GWEI, suggesting varying network congestion or user preferences.
• Receipt Status (receipt_status): The mean of 99.93% indicates a high success rate for transactions.

BTC Statistics

• Shape: 10000 rows, 9 columns

• Missing Values: None

• Data Types:

  • hash: object
  • block_number: int64
  • block_timestamp: datetime64[ns, UTC]
  • input_btc: float64
  • output_btc: float64
  • fee_btc: float64
  • input_count: int64
  • output_count: int64
  • is_coinbase: bool

• Descriptive Statistics:

	block_number	input_btc	output_btc	fee_btc	input_count	output_count
count	10000	10000	10000	10000	10000	10000
mean	925300	2.48926	2.4902	9.46632e-06	2.0699	2.7378
std	0.783679	26.2408	26.2408	2.95765e-05	9.11424	9.65371
min	925299	0	0	0	0	1
25%	925299	0.00128595	0.00128433	2.82e-06	1	1
50%	925300	0.00739055	0.00739597	4.4e-06	1	2
75%	925301	0.0630795	0.0633728	8.04e-06	1	2
max	925301	1996.61	1996.61	0.0014603	329	413

• Input Value (input_btc): Ranges from 0.000000 to 1996.609056 BTC, with an average of 2.489261 BTC. Note 0 missing values, likely from coinbase transactions or untracked inputs.
• Output Value (output_btc): Ranges from 0.000000 to 1996.609030 BTC, with an average of 2.490200 BTC. Note 0 missing values.
• Transaction Fee (fee_btc): Fees are generally low, with an average of 0.000009 BTC, and a maximum of 0.001460 BTC.
• Input Count (input_count): Average number of inputs per transaction is 2.07, indicating transactions often consolidate multiple UTXOs.
• Output Count (output_count): Average number of outputs per transaction is 2.74.

DOGE Statistics

• Shape: 10000 rows, 9 columns

• Missing Values: None

• Data Types:

  • hash: object
  • block_number: int64
  • block_timestamp: datetime64[ns, UTC]
  • input_doge: float64
  • output_doge: float64
  • fee_doge: float64
  • input_count: int64
  • output_count: int64
  • is_coinbase: bool

• Descriptive Statistics:

	block_number	input_doge	output_doge	fee_doge	input_count	output_count
count	10000	10000	10000	10000	10000	10000
mean	5.45953e+06	30977.5	30991.5	0.0715129	1.0889	1.3957
std	4.22001	1.68994e+06	1.68994e+06	0.518674	1.47561	2.78914
min	5.45952e+06	0	0.001	0	0	1
25%	5.45953e+06	0.011175	0.001	0.010175	1	1
50%	5.45953e+06	0.0114	0.001	0.0104	1	1
75%	5.45953e+06	0.0114	0.001	0.0104	1	1
max	5.45953e+06	1.62704e+08	1.62704e+08	16.878	105	61

• Input Value (input_doge): Ranges from 0.000000 to 162704181.648130 DOGE, with an average of 30977.504996 DOGE. Note 0 missing values, likely from coinbase transactions or untracked inputs.
• Output Value (output_doge): Ranges from 0.001000 to 162704176.458130 DOGE, with an average of 30991.503881 DOGE. Note 0 missing values.
• Transaction Fee (fee_doge): Fees are generally low, with an average of 0.071513 DOGE, and a maximum of 16.878000 DOGE.
• Input Count (input_count): Average number of inputs per transaction is 1.09, indicating transactions often consolidate multiple UTXOs.
• Output Count (output_count): Average number of outputs per transaction is 1.40.

BCH Statistics

• Shape: 10000 rows, 9 columns

• Missing Values:

  • input_bch: 121 missing values (1.21%)

• Data Types:

  • hash: object
  • block_number: int64
  • block_timestamp: datetime64[ns, UTC]
  • input_bch: float64
  • output_bch: float64
  • fee_bch: float64
  • input_count: int64
  • output_count: int64
  • is_coinbase: bool

• Descriptive Statistics:

	block_number	input_bch	output_bch	fee_bch	input_count	output_count
count	10000	9879	10000	10000	10000	10000
mean	845621	53.9227	53.308	0.000302823	4.9844	2.516
std	34.3983	740.315	735.843	0.00484123	39.8772	8.60367
min	845555	8.88e-06	6.14e-06	0	0	1
25%	845596	0.0278857	0.0292351	2.26e-06	1	2
50%	845621	0.499	0.501174	3.74e-06	1	2
75%	845653	4.85875	4.77461	7.68e-06	2	2
max	845676	63287.6	63287.6	0.0888528	700	460

• Input Value (input_bch): Ranges from 0.000009 to 63287.585142 BCH, with an average of 53.922684 BCH. Note 121 missing values, likely from coinbase transactions or untracked inputs.
• Output Value (output_bch): Ranges from 0.000006 to 63287.585112 BCH, with an average of 53.308031 BCH. Note 0 missing values.
• Transaction Fee (fee_bch): Fees are generally low, with an average of 0.000303 BCH, and a maximum of 0.088853 BCH.
• Input Count (input_count): Average number of inputs per transaction is 4.98, indicating transactions often consolidate multiple UTXOs.
• Output Count (output_count): Average number of outputs per transaction is 2.52.

DASH Statistics

• Shape: 10000 rows, 9 columns

• Missing Values:

  • input_dash: 457 missing values (4.57%)
  • output_dash: 72 missing values (0.72%)

• Data Types:

  • hash: object
  • block_number: int64
  • block_timestamp: datetime64[ns, UTC]
  • input_dash: float64
  • output_dash: float64
  • fee_dash: float64
  • input_count: int64
  • output_count: int64
  • is_coinbase: bool

• Descriptive Statistics:

	block_number	input_dash	output_dash	fee_dash	input_count	output_count
count	10000	9543	9928	10000	10000	10000
mean	1.87864e+06	24.519	23.6646	3.97762e-05	4.4742	4.5235
std	105.282	163.905	160.752	0.000692605	10.7281	6.74607
min	1.87846e+06	8.555e-05	0	0	0	0
25%	1.87856e+06	0.0300003	0.0499655	0	1	2
50%	1.87864e+06	1.04723	1.20001	2.27e-06	1	2
75%	1.87873e+06	11.0001	10.1067	6e-06	6	6
max	1.87884e+06	6914.14	6914.14	0.0665187	618	189

• Input Value (input_dash): Ranges from 0.000086 to 6914.138218 DASH, with an average of 24.518962 DASH. Note 457 missing values, likely from coinbase transactions or untracked inputs.
• Output Value (output_dash): Ranges from 0.000000 to 6914.138216 DASH, with an average of 23.664593 DASH. Note 72 missing values.
• Transaction Fee (fee_dash): Fees are generally low, with an average of 0.000040 DASH, and a maximum of 0.066519 DASH.
• Input Count (input_count): Average number of inputs per transaction is 4.47, indicating transactions often consolidate multiple UTXOs.
• Output Count (output_count): Average number of outputs per transaction is 4.52.

Visualization Insights

Schema Comparison Matrix

ETC Gas Price Distribution Ranges

Average Transaction Values (Native Units)

Usage Examples

This dataset is highly versatile and can be used for various analytical and research purposes:

• Transaction Pattern Analysis: Analyze transaction volumes over time, identify peak activity periods, and study the distribution of transaction sizes and fees for different cryptocurrencies.
• Fee Dynamics Research: Investigate how transaction fees are determined across different blockchain models (Account-based vs. UTXO-based), and how they correlate with network congestion or value transferred.
• Blockchain Model Comparison: Directly compare the operational characteristics and efficiency of Account-based (ETC) versus UTXO-based (BTC, DOGE, BCH, DASH) transaction models using their respective data schemas.
• Address Behavior Analysis: For ETC, study transaction flows between 'from_address' and 'to_address' to infer network participant behavior. For UTXO chains, analyze 'input_count' and 'output_count' to understand transaction complexity and UTXO management strategies.
• Impact of Coinbase Transactions: For UTXO chains, analyze 'is_coinbase' transactions to understand block reward mechanisms and their frequency.
• Anomaly Detection: Identify unusual transaction activities, such as unusually high transaction values, fees, or atypical input/output counts, which might indicate fraudulent activities or network events.

Potential Use Cases

This dataset can serve as a foundational resource for a variety of use cases in blockchain research, data science, and financial analysis:

• Blockchain Research: Investigate differences in transaction dynamics, network congestion, and fee structures between Account-based and UTXO-based blockchains. This can include studying the efficiency of different transaction models.
• Economic Analysis of Cryptocurrencies: Analyze the flow of value, transaction volume, and fee trends to understand market behavior, adoption rates, and economic health of each cryptocurrency.
• Anomaly and Fraud Detection: Develop and test algorithms to detect unusual transaction patterns, potential illicit activities, or network attacks based on transaction values, gas usage, or input/output counts.
• Wallet Analysis and User Profiling: By aggregating transactions per address (for ETC) or analyzing UTXO chains, researchers can gain insights into wallet behavior, identify large holders, or understand common transaction strategies.
• Network Performance Modeling: Use the transaction data to model and simulate network performance under various loads, optimizing for factors like transaction throughput and confirmation times.
• Educational Tool: Serve as a practical dataset for students and researchers to learn about blockchain data analysis, different cryptocurrency transaction models, and data manipulation techniques in Python.

📜 Citation

If you use this dataset in your research, please cite:

@dataset{50k_Cryptocurrency_Transaction_Dataset_by_HNM,
  title     = {50k_Cryptocurrency_Transaction_Dataset_by_HNM},
  author    = {Haq Nawaz Malik},
  year      = {2025},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/Omarrran/50k_Cryptocurrency_Transaction_Dataset_by_HNM}
}

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