By Megan Squire
ISBN-10: 1785284010
ISBN-13: 9781785284014
Key Features
- Grow your info technological know-how services via filling your toolbox with confirmed ideas for a wide selection of cleansing challenges
- Familiarize your self with the the most important information cleansing strategies, and percentage your personal fresh information units with others
- Complete real-world tasks utilizing facts from Twitter and Stack Overflow
Book Description
Is a lot of it slow spent doing tedious initiatives akin to cleansing soiled info, accounting for misplaced information, and getting ready info for use by way of others? if that is so, then having the correct instruments makes a severe distinction, and may be an outstanding funding as you develop your info technological know-how expertise.
The publication begins by way of highlighting the significance of information cleansing in information technology, and should assist you achieve rewards from reforming your cleansing procedure. subsequent, you'll cement your wisdom of the fundamental ideas that the remainder of the booklet depends on: dossier codecs, facts kinds, and personality encodings. additionally, you will find out how to extract and fresh facts kept in RDBMS, internet documents, and PDF records, via useful examples.
At the top of the publication, you'll be given an opportunity to take on a few real-world projects.
What you are going to learn
- Understand the position of knowledge cleansing within the total facts technological know-how process
- Learn the fundamentals of dossier codecs, info forms, and personality encodings to wash information properly
- Master severe positive factors of the spreadsheet and textual content editor for organizing and manipulating data
- Convert facts from one universal structure to a different, together with JSON, CSV, and a few special-purpose formats
- Implement 3 diversified concepts for parsing and cleansing info present in HTML records at the Web
- Reveal the mysteries of PDF records and pull out simply the information you want
- Develop a number of recommendations for detecting and cleansing undesirable information saved in an RDBMS
- Create your personal fresh facts units that may be packaged, authorized, and shared with others
- Use the instruments from this e-book to accomplish real-world tasks utilizing info from Twitter and Stack Overflow
About the Author
Megan Squire is a professor of computing sciences at Elon college. She has been gathering and cleansing soiled information for 2 many years. She is additionally the chief of FLOSSmole.org, a examine venture to assemble facts and study it so as to find out how loose, libre, and open resource software program is made.
Table of Contents
- Why do you want fresh Data?
- Fundamentals codecs, varieties, and Encodings
- Workhorses of fresh info Spreadsheets and textual content Editors
- Speaking the Lingua Franca information Conversions
- Collecting and cleansing information from the Web
- Cleaning facts in Pdf Files
- RDBMS cleansing Techniques
- Best Practices for Sharing Your fresh Data
- Stack Overflow Project
- Twitter Project
Read or Download Clean Data - Data Science Strategies for Tackling Dirty Data PDF
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Example text
For instance, here are a few common ways of writing the same date: • 11-23-14 • 11-23-2014 • 23-11-2014 • 2014-11-23 • 23-Nov-14 • November 23, 2014 • 23 November 2014 • Nov. 23, 2014 Regardless of our preference for writing dates, a complete date is made up of three parts: month, day, and year. Any date should be able to be parsed into these component parts. Areas of confusion with dates are usually in two areas: lack of clarity about the month signifier and a day signifier for numbers below 12, and confusion about specifying years.
We will definitely find the answer to this question. You might also want to compress your data when you share it with others. How can you figure out which compression method is the best choice? Archive files An archive file is simply a single file that contains many files inside it. The files inside can be either text or binary or a mixture of both. Archive files are created by a special program that takes a list of files and changes them into a single file. Of course, the archive files are created in such a way that they can be expanded back into many files.
Any date should be able to be parsed into these component parts. Areas of confusion with dates are usually in two areas: lack of clarity about the month signifier and a day signifier for numbers below 12, and confusion about specifying years. For example, if we only see "11-23", we can assume November 23, as there is no month abbreviated "23", but what year is it? If we see a date of "11-12", is that the 12th of November or the 11th of December? And in what year? Does a year of 38 signify 1938 or 2038?