Megan Squire's Clean Data - Data Science Strategies for Tackling Dirty Data PDF

By Megan Squire

Key Features

  • Grow your info technology services by way of filling your toolbox with confirmed recommendations for a wide selection of cleansing challenges
  • Familiarize your self with the an important information cleansing approaches, and percentage your personal fresh information units with others
  • Complete real-world initiatives utilizing facts from Twitter and Stack Overflow

Book Description

Is a lot of it slow spent doing tedious initiatives corresponding to cleansing soiled facts, accounting for misplaced information, and getting ready info for use by way of others? if this is the case, then having the precise instruments makes a serious distinction, and should be an outstanding funding as you develop your info technology expertise.

The e-book begins through highlighting the significance of knowledge cleansing in information technology, and should make it easier to acquire rewards from reforming your cleansing procedure. subsequent, you are going to cement your wisdom of the fundamental innovations that the remainder of the ebook is determined by: dossier codecs, facts varieties, and personality encodings. additionally, you will methods to extract and fresh facts saved in RDBMS, net records, and PDF records, via functional examples.

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

What you are going to learn

  • Understand the position of information cleansing within the total info technological know-how process
  • Learn the fundamentals of dossier codecs, information forms, and personality encodings to scrub facts properly
  • Master serious positive aspects of the spreadsheet and textual content editor for organizing and manipulating data
  • Convert facts from one universal layout to a different, together with JSON, CSV, and a few special-purpose formats
  • Implement 3 diverse suggestions for parsing and cleansing information present in HTML records at the Web
  • Reveal the mysteries of PDF files and the way to pull out simply the knowledge you want
  • Develop more than a few suggestions for detecting and cleansing undesirable information kept in an RDBMS
  • Create your individual fresh information units that may be packaged, approved, and shared with others
  • Use the instruments from this ebook 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 accumulating and cleansing soiled info for 2 a long time. She is additionally the chief of, a study venture to gather information and study it with the intention to learn the way unfastened, libre, and open resource software program is made.

Table of Contents

  1. Why do you want fresh Data?
  2. Fundamentals codecs, forms, and Encodings
  3. Workhorses of fresh info Spreadsheets and textual content Editors
  4. Speaking the Lingua Franca information Conversions
  5. Collecting and cleansing information from the Web
  6. Cleaning facts 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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Sample text

We also talk about converting between data types and how to safely convert without losing information (or at least understanding the risks beforehand). This section also covers the mysterious world of empties, nulls, and blanks. We explore the various types of missing data and describe how missing data can negatively affect results of data analysis. We will compare choices and trade-offs for handling the missing data and some of the pros and cons of each method. [ 29 ] Fundamentals – Formats, Types, and Encodings As much of our data will be stored as strings, we will learn to identify different character encodings and some of the common formats you will encounter with real-world data.

How do we know which program to use to uncompress the file? The first and biggest clue is the file's extension. This is a key tip-off as to what compression program created the file. Knowing how to uncompress the file is dependent on knowing how it was compressed. In Windows, you can see the installed program that is associated with your file extension by right-clicking on the file and choosing Properties. Then, look for the Open With option to see which program Windows thinks will uncompress the file.

Note that there is a + sign to represent the space character, as URLs do not allow spaces. The iTunes API returns 50 results from its music database for my search keywords. The entire set is formatted as a JSON object. As with all JSON objects, it is formatted as a collection of name-value pairs. The JSON returned in this example appears very long, because there are 50 results returned, but each result is actually very simplistic—there are no multivalue attributes or even any hierarchical data in the iTunes data shown in this URL.

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