Data Wrangling with JavaScript – eBook

eBook details

  • Author: Ashley Davis
  • File Size: 14 MB
  • Format: PDF
  • Length: 432 pages
  • Publisher: Manning Publications; 1st edition
  • Publication Date: December 17, 2018
  • Language: English
  • ISBN-10: 1617294845
  • ISBN-13: 9781617294846


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Ashley Davis


Data Wrangling with JavaScript (PDF) 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.

This purchase only includes a eBook in PDF without any restrictions.

About the Technology

Why not handle your data analysis in JavaScript? Modern libraries and data handling techniques mean you can collect, store, process, clean, 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 eBook

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

What is inside the ebook

  • Handling unusual data sets
  • Establishing a data pipeline
  • Storage, acquisition, and retrieval
  • Preparing and cleaning raw dataInteractive visualizations with D3

About the Author

Ashley Davis is an entrepreneur, software developer, 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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