Market Dataset

Catalog

Unlabeled Dataset

Ether Price and Volume Dataset

Bitcoin Price and Volume Dataset

Mt.Gox Leaked Transaction

Activity Information of DApps

Ether Price and Volume Dataset

Introduction

This is the market data of Ether in terms of price and volume from August 2015 (when Ether first appeared) to March 2019. The time interval of sampling is selected as four-hour, that is to say, we choose every kinds of price and volume every of four-hour as the original data.

The original market data of Ether are obtained from Poloniex,one of the most active crypto asset exchanges.

Data details

About this table
Market data about Ether as the exchange rate is ETH/USDT.
Columns (8 columns)
close The close price in the period
date The timestamp in the beginning of this period
high The highest price in the period
low The lowest price in the period
open The open price in the period
quoteVolume The quote volume in the period
volume The base volume in the period
weightedVolume The average price for those base volume and quote volume

Citation

BibTeX

@article{han2020long,
title={Long-range dependence, multi-fractality and volume-return causality of Ether market},
author={Han, Qing and Wu, Jiajing and Zheng, Zibin},
journal={Chaos: An Interdisciplinary Journal of Nonlinear Science},
volume={30},
number={1},
pages={011101},
year={2020},
publisher={AIP Publishing LLC}
}

IEEE

Q. Han, J. Wu and Z. Zheng, “Long-range dependence, multi-fractality and volume-return causality of Ether market,” Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 30, no. 1, pp. 011101, 2020.

ACM

Qing Han, Jiajing Wu and Zibin Zheng, “Long-range dependence, multi-fractality and volume-return causality of Ether market,” Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 30, no. 1, pp. 011101, 2020.

Bitcoin Price and Volume Dataset

Introduction

This is the market data of Bitcoin in terms of price and volume from August 2015 (when Ether first appeared) to March 2019. The time interval of sampling is selected as four-hour, that is to say, we choose every kinds of price and volume every of four-hour as the original data.

The original market data of Bitcoin are obtained from Poloniex,one of the most active crypto asset exchanges.

Data details

About this table
Market data about Bitcoin as the exchange rate is BTC/USDT.
Columns (8 columns)
close The close price in the period
date The timestamp in the beginning of this period
high The highest price in the period
low The lowest price in the period
open The open price in the period
quoteVolume The quote volume in the period
volume The base volume in the period
weightedVolume The average price for those base volume and quote volume

Citation

BibTeX

@article{han2020long,
title={Long-range dependence, multi-fractality and volume-return causality of Ether market},
author={Han, Qing and Wu, Jiajing and Zheng, Zibin},
journal={Chaos: An Interdisciplinary Journal of Nonlinear Science},
volume={30},
number={1},
pages={011101},
year={2020},
publisher={AIP Publishing LLC}
}

IEEE

Q. Han, J. Wu and Z. Zheng, “Long-range dependence, multi-fractality and volume-return causality of Ether market,” Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 30, no. 1, pp. 011101, 2020.

ACM

Qing Han, Jiajing Wu and Zibin Zheng, “Long-range dependence, multi-fractality and volume-return causality of Ether market,” Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 30, no. 1, pp. 011101, 2020.

Mt.Gox Leaked Transaction

Introduction

This data set is the transaction data leaked by mt.gox exchange. First, we combine the buy and sell transaction fields of the same transaction, and then de duplicate them through transaction time, transaction account, etc. to ensure the uniqueness of each transaction data. This transaction data is very useful for analyzing the user behavior of bitcoin market. 

We have done a market manipulation study using this data set. You can see related research for details.

Data details

About this table
Transactions of bitcoin market.
Columns (8 columns)
Source The user who sell bitcoins
Target The user who buy bitcoins
Trade_Id The ID of present trasaction
Bitcoins Number of bitcoins involved in the current transaction
Money Dollars spent buying bitcoins
Money_rate Price per bitcoin
Date Date of transaction
label Types of users

Citation

BibTeX

@inproceedings{chen2019market, 
title={Market Manipulation of Bitcoin: Evidence from Mining the Mt. Gox Transaction Network},
author={Chen, Weili and Wu, Jun and Zheng, Zibin and Chen, Chuan and Zhou, Yuren},
booktitle={IEEE Conference on Computer Communications},
pages={964--972},
year={2019},
organization={IEEE}
}

IEEE

W. Chen, J. Wu, Z. Zheng, C. Chen, and Y. Zhou, “Market Manipulation of Bitcoin: Evidence from Mining the Mt. Gox Transaction Network,” Proc. - IEEE INFOCOM, vol. 2019-April, no. April 2011, pp. 964–972, 2019, doi: 10.1109/INFOCOM.2019.8737364.

ACM

Weili Chen, Jun Wu, Zibin Zheng, Chuan Chen, and Yuren Zhou. 2019. Market Manipulation of Bitcoin: Evidence from Mining the Mt. Gox Transaction Network. Proceedings - IEEE INFOCOM 2019-April, April 2011: 964–972. https://doi.org/10.1109/INFOCOM.2019.8737364

Activity Information of DApps

Introduction

Blockchain-based decentralized applications (DApp) is an application that enables end users to interact directly with blockchain. Generally, It consists of two parts: web pages as front end, and smart contracts as back end.

There are a number of DApps on platforms like Ethereum, EOS, Steem and so on. Some of them are always active (s.t., there are always new transactions corresponding to those DApps), while some of them are seemingly dead for a long time.

This dataset contains two files, one for DappRadar and the other for State of the Dapps.

The dataset provides information about dapps’ activity, such as their transaction counts, total transaction values and active users in 24 hours, 7 days and 30 days.

Data details

About this table
Activity information of DApps on DappRadar.
Columns (15 columns)
link Link to the DApp
name DApp name
Txs_24h Transaction count of that DApp in 24 hours
Txs_7d Transaction count of that DApp in 7 days
balance Account balance as of Sep 13, 2019
category Type of the DApp
protocol DApp protocol
rank DApp rank as of Sep 13, 2019
users_24h Active users of the DApp in 24 hours
volume_24h Volume of that DApp in 24 hours
volume_7d Volume of that DApp in 7 days
long_intro Introduction of the DApp
other_link Other important links
submitted Time when DApp was submitted to the market
contract Contracts contained in that DApp
About this table
Activity information of DApps on State of the Dapps.
Columns (28 columns)
link Link to the DApp
name DApp name
category Type of the DApp
dev_activity_30d Dev activity in 30 days
platform DApp platform
rank DApp rank as of Sep 13, 2019
users_24h Active users of the DApp in 24 hours
volume_7d Active users of the DApp in 7 days
short_intro Brief introduction of the DApp
long_intro Introduction of the DApp
status DApp status
author App authors
software_license Software license
submitted_updated Submitted date
mainnet Mainnet
contract Contract addresses contained in that DApp
tag DApp tags
last_updated Last updated date
transaction_count Transaction count of that DApp
transaction_count_volume_greater_0 Nonzero transaction count
transaction_count_ratio The ratio of nonzero transactions
total_transaction_volume_ether Total transaction volume in ethers
contract_count Contract count
dapp_total_loss The DApp’s net income
user_count_unique_remove_contract_creator Unique users count, contract creator not included
user_total_loss User total net income
user_loss_ratio User income ratio
user_loss_average Average user net income

Citation

BibTeX

@misc{xblockEOS,
author = {Kong, Queping and Chen, Xiangping and Zheng, Zibin},
title = {{XBLOCK Blockchain Datasets}: {InPlusLab} EOS DApps Datasets},
howpublished = {\url{http://xblock.pro/eos/}},
month = Nov,
year = 2019
}

IEEE

Q. Kong, X. Chen, Z. Zheng “{XBLOCK Blockchain Datasets}: {InPlusLab} EOS DApps Datasets,” \url{http://xblock.pro/eos/}, Accessed: Nov 2019.

ACM

Queping Kong, Xiangping Chen, Zibin Zheng “{XBLOCK Blockchain Datasets}: {InPlusLab} EOS DApps Datasets,” \url{http://xblock.pro/eos/}, Accessed: Nov 2019.

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