Clean Data - Data Science Strategies for Tackling Dirty Data pdf epub mobi txt 电子书 下载 2025
- 计算机
- 计算机科学
- 英文版
- Programming
- Data
- 数据
- datascience
- data.mining
- 数据清洗
- 数据质量
- 数据科学
- 数据分析
- 数据预处理
- 机器学习
- Python
- R
- 数据工程
- 统计学
具体描述
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.
作者简介
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.
目录信息
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
· · · · · · (收起)
读后感
评分
评分
评分
评分
用户评价
书侧重于数据采集，与题名不符
评分怀疑看了假书
评分书侧重于数据采集，与题名不符
评分书侧重于数据采集，与题名不符
评分书侧重于数据采集，与题名不符
相关图书
本站所有内容均为互联网搜索引擎提供的公开搜索信息，本站不存储任何数据与内容，任何内容与数据均与本站无关，如有需要请联系相关搜索引擎包括但不限于百度，google,bing,sogou 等
© 2025 book.quotespace.org All Rights Reserved. 小美书屋 版权所有