Clean Data - Data Science Strategies for Tackling Dirty Data pdf epub mobi txt 電子書 下載2025
- 計算機
- 計算機科學
- 英文版
- Programming
- Data
- 數據
- datascience
- data.mining
- 數據清洗
- 數據質量
- 數據科學
- 數據分析
- 數據預處理
- 機器學習
- Python
- R
- 數據工程
- 統計學
具體描述
Is much of your time spent doing tedious tasks such as cleaning dirty data, accounting for lost data, and preparing data to be used by others? If so, then having the right tools makes a critical difference, and will be a great investment as you grow your data science expertise.
The book starts by highlighting the importance of data cleaning in data science, and will show you how to reap rewards from reforming your cleaning process. Next, you will cement your knowledge of the basic concepts that the rest of the book relies on: file formats, data types, and character encodings. You will also learn how to extract and clean data stored in RDBMS, web files, and PDF documents, through practical examples.
At the end of the book, you will be given a chance to tackle a couple of real-world projects.
著者簡介
Megan Squire is a professor of computing sciences at Elon University. She has been collecting and cleaning dirty data for two decades. She is also the leader of FLOSSmole.org, a research project to collect data and analyze it in order to learn how free, libre, and open source software is made.
圖書目錄
1. Why Do You Need Clean Data?
2. Fundamentals – Formats, Types, and Encodings
3. Workhorses of Clean Data – Spreadsheets and Text Editors
4. Speaking the Lingua Franca – Data Conversions
5. Collecting and Cleaning Data from the Web
6. Cleaning Data in Pdf Files
7. RDBMS Cleaning Techniques
8. Best Practices for Sharing Your Clean Data
9. Stack Overflow Project
10. Twitter Project
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