Clean Data - Data Science Strategies for Tackling Dirty Data by Megan Squire

By Megan Squire

Key Features

  • Grow your info technology services through filling your toolbox with confirmed concepts for a large choice of cleansing challenges
  • Familiarize your self with the the most important info cleansing strategies, and percentage your individual fresh information units with others
  • Complete real-world initiatives utilizing facts from Twitter and Stack Overflow

Book Description

Is a lot of a while spent doing tedious projects reminiscent of cleansing soiled facts, accounting for misplaced info, and getting ready information for use by means of others? if that is so, then having the best instruments makes a severe distinction, and should be an excellent funding as you develop your info technology expertise.

The publication starts off via highlighting the significance of knowledge cleansing in information technological know-how, and may assist you to achieve rewards from reforming your cleansing procedure. subsequent, you are going to cement your wisdom of the elemental ideas that the remainder of the publication is dependent upon: dossier codecs, info forms, and personality encodings. additionally, you will easy methods to extract and fresh info saved in RDBMS, internet records, and PDF files, via useful examples.

At the tip of the ebook, you can be given an opportunity to take on a few real-world projects.

What you'll learn

  • Understand the function of information cleansing within the total information technology process
  • Learn the fundamentals of dossier codecs, info kinds, and personality encodings to wash info properly
  • Master serious positive factors of the spreadsheet and textual content editor for organizing and manipulating data
  • Convert information from one universal layout to a different, together with JSON, CSV, and a few special-purpose formats
  • Implement 3 various techniques for parsing and cleansing facts present in HTML records at the Web
  • Reveal the mysteries of PDF records and find out how to pull out simply the knowledge you want
  • Develop various strategies for detecting and cleansing undesirable facts kept in an RDBMS
  • Create your individual fresh information units that may be packaged, approved, and shared with others
  • Use the instruments from this e-book to accomplish real-world initiatives utilizing info from Twitter and Stack Overflow

About the Author

Megan Squire is a professor of computing sciences at Elon college. She has been amassing and cleansing soiled facts for 2 a long time. She can also be the chief of FLOSSmole.org, a examine undertaking to gather facts and research it with the intention to find out how unfastened, libre, and open resource software program is made.

Table of Contents

  1. Why do you want fresh Data?
  2. Fundamentals codecs, kinds, and Encodings
  3. Workhorses of unpolluted info Spreadsheets and textual content Editors
  4. Speaking the Lingua Franca facts Conversions
  5. Collecting and cleansing info from the Web
  6. Cleaning information in Pdf Files
  7. RDBMS cleansing Techniques
  8. Best Practices for Sharing Your fresh Data
  9. Stack Overflow Project
  10. Twitter Project

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Additional resources for Clean Data - Data Science Strategies for Tackling Dirty Data

Sample text

Tar Compression options When compressing and uncompressing, there are many other options you should take into consideration in order to make your data cleaning job easier: • Do you want to compress a file and also keep the original? By default, most compression and archiving programs will remove the original file. If you want to keep the original file and also create a compressed version of it, you can usually specify this. • Do you want to add new files to an existing compressed file? There are options for this in most archiving and compression programs.

Sometimes, this is called updating or replacing. • Do you want to encrypt the compressed file and require a password to open it? Many compression programs provide an option for this. • When uncompressing, do you want to overwrite files in the directory with the same name? Look for a force option. Depending on which compression software you are using and what its options are, you can use many of these options to make the job of dealing with files easier. This is especially true with large files—either large in size or large in number!

For example, a DBMS may allow us to declare whether we will be storing floatingpoint numbers, decimal numbers, and currency/money numbers at the time we set up our database. Each of these will act slightly differently—in math problems, for instance. We will need to read the guidance provided by the DBMS for each data type and stay on top of changes. Many times, the DBMS provider will change the specifications for a particular data type because of memory concerns or the like. Spreadsheet applications, on the other hand, unlike DBMS applications, are designed to display data in addition to just storing it.

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