Data Wrangling with JavaScript

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Data Wrangling with JavaScript image
ISBN-10:

1617294845

ISBN-13:

9781617294846

Author(s): Davis, Ashley
Edition: First Edition
Released: Dec 17, 2018
Publisher: Manning
Format: Paperback, 432 pages

Description:

Summary

Data Wrangling with JavaScript is hands-on guide that will teach you how to create a JavaScript-based data processing pipeline, handle common and exotic data, and master practical troubleshooting strategies.

Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

About the Technology

Why not handle your data analysis in JavaScript? Modern libraries and data handling techniques mean you can collect, clean, process, store, visualize, and present web application data while enjoying the efficiency of a single-language pipeline and data-centric web applications that stay in JavaScript end to end.

About the Book

Data Wrangling with JavaScript promotes JavaScript to the center of the data analysis stage! With this hands-on guide, you'll create a JavaScript-based data processing pipeline, handle common and exotic data, and master practical troubleshooting strategies. You'll also build interactive visualizations and deploy your apps to production. Each valuable chapter provides a new component for your reusable data wrangling toolkit.

What's inside

  • Establishing a data pipeline
  • Acquisition, storage, and retrieval
  • Handling unusual data sets
  • Cleaning and preparing raw dataInteractive visualizations with D3

About the Reader

Written for intermediate JavaScript developers. No data analysis experience required.

About the Author

Ashley Davis is a software developer, entrepreneur, author, and the creator of Data-Forge and Data-Forge Notebook, software for data transformation, analysis, and visualization in JavaScript.

Table of Contents

  1. Getting started: establishing your data pipeline
  2. Getting started with Node.js
  3. Acquisition, storage, and retrieval
  4. Working with unusual data
  5. Exploratory coding
  6. Clean and prepare
  7. Dealing with huge data files
  8. Working with a mountain of data
  9. Practical data analysis
  10. Browser-based visualization
  11. Server-side visualization
  12. Live data
  13. Advanced visualization with D3
  14. Getting to production

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