Pearson Education

Data Visualization Toolkit

Edition: 1st Edition
Subjects: ICT, Programming & scripting languages: general
ISBN13: 9780134465258
Published: 04 Aug 2016

Format -
By Barrett Clark

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Regular price A$46.23
Sale price A$46.23 Regular price A$47.66

Data Visualization Toolkit

Regular price A$46.23
Sale price A$46.23 Regular price A$47.66
Product description

Barrett Clark teaches through real-world problems and examples developed specifically to illuminate every technique you need to generate stunningly effective visualisations. You’ll move from the absolute basics toward deep dives, mastering diverse visualisations and discovering when to use each. Along the way, you’ll build three start-to-finish visualisation applications, using actual real estate, weather, and travel datasets.

 

Clark addresses every component of data visualisation: your data, database, application server, visualisation libraries, and more. He explains data transformations; presents expert techniques in JavaScript, Ruby, and SQL; and illuminates key concepts associated with both descriptive statistics and geospatial data. Throughout, everything is aimed at one goal: to help you cut through the clutter and let your data tell all it can.

 

This guide will help you

  • Explore and understand the data visualisation technology stack
  • Master the thought process and steps involved in importing data
  • Extract, transform, and load data in usable, reliable form
  • Handle spotty data, or data that doesn’t line up with what your chart expects
  • Use D3 to build pie and bar charts, scatter and box plots, and more
  • Work effectively with time-series data
  • Tweak Ruby and SQL to optimise performance with large datasets
  • Use raw SQL in Rails: window functions, subqueries, and common table expressions
  • Build chord diagrams and time-series aggregates
  • Use separate databases or schema for reporting databases
  • Integrate geographical data via geospatial SQL queries
  • Construct maps with Leaflet and Rails
  • Query geospatial data the “Rails way” and the “raw SQL way”

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