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Data Wrangling with JavaScript
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 data wrangling needs!
Data Wrangling with JavaScript teaches readers core data munging techniques in JavaScript, along with many libraries and tools that will make their data tasks even easier.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Data Wrangling with JavaScript teaches readers core data munging techniques in JavaScript, along with many libraries and tools that will make their data tasks even easier.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
375 pages, Paperback
Published October 30, 2018
6 people are currently reading
39 people want to read
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Displaying 1 of 1 review
February 27, 2019
I reviewed the book in early releases before the product was finished. I’ve received the final complete copy of the book in e-book and physical form.
Data science is not often associated with JavaScript. We think of the two at opposite ends. Data science is a large scale intense processing project requiring special software languages to efficiently manipulate data. JavaScript is usually used for client side scripting of light web applications in browsers.
An early part of the book briefly deals with the objections expected with using JavaScript for data work. The author is aware of Python and other technology, and compares JavaScript to the standards favourably.
A theme throughout the book is that data is handled in cycles of acquire, store, and refer. These are further broken into issues such as cleaning the data, the use of live data, and visualization.
The book uses JavaScript, Node.js, Nightmare, and D3, for the data but references other tools that can be used such as databases and Excel.
The tone of the book is conversational and expert. JavaScript is well explained so readers do not need a great deal of experience. The setup and use of each part is explained as it is needed. The book builds from setting up the JavaScript node.js environment slowly then eventually reaches advanced visualization and production maintenance.
The book is excellent for those interested in JavaScript or data science. It offers practical work with observable results.
Data science is not often associated with JavaScript. We think of the two at opposite ends. Data science is a large scale intense processing project requiring special software languages to efficiently manipulate data. JavaScript is usually used for client side scripting of light web applications in browsers.
An early part of the book briefly deals with the objections expected with using JavaScript for data work. The author is aware of Python and other technology, and compares JavaScript to the standards favourably.
A theme throughout the book is that data is handled in cycles of acquire, store, and refer. These are further broken into issues such as cleaning the data, the use of live data, and visualization.
The book uses JavaScript, Node.js, Nightmare, and D3, for the data but references other tools that can be used such as databases and Excel.
The tone of the book is conversational and expert. JavaScript is well explained so readers do not need a great deal of experience. The setup and use of each part is explained as it is needed. The book builds from setting up the JavaScript node.js environment slowly then eventually reaches advanced visualization and production maintenance.
The book is excellent for those interested in JavaScript or data science. It offers practical work with observable results.
Displaying 1 of 1 review