You're reading from Data Science for Web3 A comprehensive guide to decoding blockchain data with data analysis basics and machine learning cases

Product type Paperback

Published in Dec 2023

Publisher Packt

ISBN-13 9781837637546

Length 344 pages

Edition 1st Edition

Languages

Python

Tools

Blockchain

Concepts

Blockchain

Author (1):

Gabriela Castillo Areco

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Table of Contents (23) Chapters

Preface

1. Part 1 Web3 Data Analysis Basics

2. Chapter 1: Where Data and Web3 Meet FREE CHAPTER

3. Chapter 2: Working with On-Chain Data

4. Chapter 3: Working with Off-Chain Data

5. Chapter 4: Exploring the Digital Uniqueness of NFTs – Games, Art, and Identity

6. Chapter 5: Exploring Analytics on DeFi

7. Part 2 Web3 Machine Learning Cases

8. Chapter 6: Preparing and Exploring Our Data

9. Chapter 7: A Primer on Machine Learning and Deep Learning

10. Chapter 8: Sentiment Analysis – NLP and Crypto News

11. Chapter 9: Generative Art for NFTs

12. Chapter 10: A Primer on Security and Fraud Detection

13. Chapter 11: Price Prediction with Time Series

14. Chapter 12: Marketing Discovery with Graphs

15. Part 3 Appendix

16. Chapter 13: Building Experience with Crypto Data – BUIDL

17. Chapter 14: Interviews with Web3 Data Leaders

18. Index

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19. Other Books You May Enjoy

Appendix 1

1. Appendix 2

2. Appendix 3

The dataset

The dataset comprises a series of transactions with destinations set to Binance or OpenSea. These entities are served by multiple addresses, and for the sake of simplicity, we have selected one among the many associated with them.

The Binance 14 address (0x28c6c06298d514db089934071355e5743bf21d60) represents a Binance hot wallet that is used to facilitate the connection between the centralized exchange and Ethereum. The funds in this wallet serve deposits and withdrawals outside of Binance.

On the other hand, the address for OpenSea, specifically Wyvern Exchange v2 (0x7f268357a8c2552623316e2562d90e642bb538e5), corresponds to the marketplace contract for OpenSea.

To replicate this dataset using Flipside, we can use the following query:

sql =SELECT from_address, to_address, tx_hash
FROM ethereum.core.fact_transactions
WHERE block_timestamp >= '2023-01-01T00:00:00.000Z'
  and   block_timestamp <= '2023-06-01T00:00:00...

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You're reading from Data Science for Web3 A comprehensive guide to decoding blockchain data with data analysis basics and machine learning cases

Table of Contents (23) Chapters

The dataset

Authors (1)

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Table of Contents (23) Chapters

The dataset

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Authors (1)

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