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Data Wrangling with JavaScript
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Data Wrangling with JavaScript

Book Details

Format Paperback / Softback
ISBN-10 1617294845
ISBN-13 9781617294846
Publisher Manning Publications
Imprint Manning Publications
Country of Manufacture US
Country of Publication GB
Publication Date Mar 29th, 2019
Print length 432 Pages
Weight 748 grams
Dimensions 23.30 x 18.80 x 2.20 cms
Ksh 7,300.00
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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.

 

Key Features

·   How to handle unusual data sets

·   Cleaning and preparing raw data

·   Visualizing your results

 

Audience

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

 

Author Bio

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.

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.

 

Key Features

·   How to handle unusual data sets

·   Cleaning and preparing raw data

·   Visualizing your results

 

Audience

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

 

Author Bio

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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