Data Wrangling with JavaScript
Ashley Davis
  • MEAP began January 2018
  • Publication in Fall 2018 (estimated)
  • ISBN 9781617294846
  • 375 pages (estimated)
  • printed in black & white
If you're a JavaScript developer, you already know that working with data is a big deal. Why let the Python and R coders get all the glory? JavaScript isn't just good at data visualization, you can move your entire data wrangling pipeline to JavaScript and work more effectively. Data Wrangling with JavaScript teaches you core data munging techniques in JavaScript, along with many libraries and tools that will make your data tasks even easier.

"It's as if the author was really showing us every step. Reading seems like doing."

~ David Krief

"This is a good guide for javascript programmers who need to work data wrangling into their development pipeline."

~ Anonymous reviewer

"Not only did I learn the data pipeline around data analysis, but also details on concepts and tools I've either heard of or thought I knew. This book is not only insightful but also invaluable to developers that need to analyze data; especially in the Javascript domain!"

~ James Wang

Table of Contents detailed table of contents

1. Getting started: establishing your data pipeline

1.1. What is data wrangling?

1.2. Why a book on JavaScript data wrangling?

1.3. What will you get out of this book?

1.4. Why use JavaScript for data wrangling?

1.5. Is JavaScript appropriate for data analysis?

1.6. Navigating the JavaScript ecosystem

1.7. Assembling your toolbox

1.8. Establishing your data pipeline

1.8.1. Setting the stage

1.8.2. The data wrangling process

1.8.3. Planning

1.8.4. Acquisition, storage and retrieval

1.8.5. Exploratory coding

1.8.6. Clean and prepare

1.8.7. Analysis

1.8.8. Visualization

1.8.9. Getting to production

1.9. Summary

2. Getting started with Node.js

2.1. Starting your toolkit

2.2. Building a simple reporting system

2.3. Getting the code

2.4. Installing Node.js

2.5. Working with Node.js

2.5.1. Creating a Node.js project

2.5.2. Creating a command line application

2.5.3. Creating a code library

2.5.4. Creating a simple web server

2.6. Asynchronous coding primer

2.6.1. Loading a single file

2.6.2. Loading multiple files

2.6.3. Error handling

2.6.4. Asynchronous coding with promises

2.6.5. Wrapping asynchronous operations in promises

2.6.6. Coming soon to a JavaScript near you: “async” and “await”

2.7. Summary

3. Acquisition, storage and retrieval

3.1. Building out your toolkit

3.2. Getting the code and data

3.3. The core data representation

3.3.1. The earthquakes web site

3.3.2. Conversion between various data formats

3.4. Importing data

3.4.1. Loading data from text files

3.4.2. Loading data from a REST API

3.4.3. ParsingJSON text data

3.4.4. ParsingCSVtext data

3.4.5. Importing data from databases

3.4.6. Importing data from MongoDB

3.4.7. Importing data from MYSQL

3.5. Exporting data

3.5.1. We need some data to export!

3.5.2. Exporting data to text files

3.5.3. Exporting data to JSON text files

3.5.4. Exporting data to CSV text files

3.5.5. Exporting data to a database

3.5.6. Exporting data to MongoDB

3.5.7. Exporting data to MySQL

3.6. Building complete data conversions

3.7. Expanding the process

3.8. Summary

4. Working with unusual data sets

5. Explore and understand

6. Clean and prepare

7. Dealing with huge data files

8. Working with a mountain of data

9. Data analysis

10. Visualize and understand

11. Reporting

12. Live data*

13. Getting to production


Appendix A: JavaScript cheat sheet

Appendix B: Data-Forge cheat sheet

Appendix C: Data wrangling toolset

Appendix D: Getting Started with Vagrant

About the Technology

JavaScript is capable of handling most common data collection, cleaning, analysis and presentation tasks just as easily as R or Python. With a growing ecosystem of tools and libraries available, and the flexibility to run on many platforms (web, desktop and mobile), JavaScript is a terrific all-round environment for all your data wrangling needs!

About the book

Data Wrangling with JavaScript teaches you the art of collecting, managing, cleaning, and analyzing data with JavaScript. In this practical book written with existing JavaScript developers in mind, you'll start by setting up your JavaScript and Node.js-based data wrangling pipeline. Then, you'll systematically work through core techniques for acquiring, storing, and retrieving data of all sorts, ranging from text and .csv files to databases and REST APIs. You'll explore JavaScript-based data tools like Globby and Data-Forge, manipulate huge datasets with Node.js, and deal with strange data types including web scraping and custom binary files. Master data wrangler Ashley Davis guides you through the most important data analysis skills and teaches you how to explore, understand and visualize your data. Because you'll be using real-world data at each step of the process, you'll be confident that you can apply your new skills immediately.

What's inside

  • Establishing a data pipeline
  • Acquisition, storage, and retrieval
  • How to handle unusual data sets
  • Cleaning and preparing raw data
  • Visualizing your results

About the reader

Written for developers with experience using JavaScript. No prior knowledge of data analytics is needed.

About the author

Ashley Davis is a software developer, entrepreneur, writer, and a stock trader. He is the creator of Data-Forge, a data transformation and analysis toolkit for JavaScript inspired by Pandas and Microsoft LINQ.

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