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Data Wrangling with JavaScript
Ashley Davis
出版
Simon and Schuster
, 2018-12-02
主題
Computers / Data Science / General
Computers / Data Science / Data Analytics
Computers / Data Science / Data Warehousing
Computers / Languages / JavaScript
ISBN
1638351139
9781638351139
URL
http://books.google.com.hk/books?id=YjszEAAAQBAJ&hl=&source=gbs_api
EBook
SAMPLE
註釋
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
Getting started: establishing your data pipeline
Getting started with Node.js
Acquisition, storage, and retrieval
Working with unusual data
Exploratory coding
Clean and prepare
Dealing with huge data files
Working with a mountain of data
Practical data analysis
Browser-based visualization
Server-side visualization
Live data
Advanced visualization with D3
Getting to production