دانلود کتاب Clean Data - Data Science Strategies for Tackling Dirty Data

Key FeaturesGrow your data science expertise by filling your toolbox with proven strategies for a wide variety of cleaning challengesFamiliarize yourself with the crucial data cleaning processes, and share your own clean data sets with othersComplete real-world projects using data from Twitter and Stack OverflowBook DescriptionIs 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.What you will learnUnderstand the role of data cleaning in the overall data science processLearn the basics of file formats, data types, and character encodings to clean data properlyMaster critical features of the spreadsheet and text editor for organizing and manipulating dataConvert data from one common format to another, including JSON, CSV, and some special-purpose formatsImplement three different strategies for parsing and cleaning data found in HTML files on the WebReveal the mysteries of PDF documents and learn how to pull out just the data you wantDevelop a range of solutions for detecting and cleaning bad data stored in an RDBMSCreate your own clean data sets that can be packaged, licensed, and shared with othersUse the tools from this book to complete two real-world projects using data from Twitter and Stack OverflowAbout the AuthorMegan 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.Table of ContentsWhy Do You Need Clean Data?Fundamentals Formats, Types, and EncodingsWorkhorses of Clean Data Spreadsheets and Text EditorsSpeaking the Lingua Franca Data ConversionsCollecting and Cleaning Data from the WebCleaning Data in Pdf FilesRDBMS Cleaning TechniquesBest Practices for Sharing Your Clean DataStack Overflow ProjectTwitter Project