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Building Data-Driven Applications with Danfo.js

Building Data-Driven Applications with Danfo.js

By : Odegua, Oni
3.8 (4)
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Building Data-Driven Applications with Danfo.js

Building Data-Driven Applications with Danfo.js

3.8 (4)
By: Odegua, Oni

Overview of this book

Most data analysts use Python and pandas for data processing for the convenience and performance these libraries provide. However, JavaScript developers have always wanted to use machine learning in the browser as well. This book focuses on how Danfo.js brings data processing, analysis, and ML tools to JavaScript developers and how to make the most of this library to build data-driven applications. Starting with an overview of modern JavaScript, you’ll cover data analysis and transformation with Danfo.js and Dnotebook. The book then shows you how to load different datasets, combine and analyze them by performing operations such as handling missing values and string manipulations. You’ll also get to grips with data plotting, visualization, aggregation, and group operations by combining Danfo.js with Plotly. As you advance, you’ll create a no-code data analysis and handling system and create-react-app, react-table, react-chart, Draggable.js, and tailwindcss, and understand how to use TensorFlow.js and Danfo.js to build a recommendation system. Finally, you’ll build a Twitter analytics dashboard powered by Danfo.js, Next.js, node-nlp, and Twit.js. By the end of this app development book, you’ll be able to build and embed data analytics, visualization, and ML capabilities into any JavaScript app in server-side Node.js or the browser.
Table of Contents (18 chapters)
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1
Section 1: The Basics
3
Section 2: Data Analysis and Manipulation with Danfo.js and Dnotebook
10
Section 3: Building Data-Driven Applications

Chapter 5: Data Visualization with Plotly.js

Plotting and visualization are very important tasks in data analysis, and as such, we are dedicating a full chapter to them. A data analyst will typically perform plotting and data visualization as part of the exploratory data analysis (EDA) phase. This can greatly help in identifying useful patterns hidden in data and in building intuition for data modeling.

In this chapter, you will learn how to use Plotly.js to create rich and interactive plots that can be embedded into any web application.

Specifically, we'll cover the following topics:

  • A brief primer on Plotly.js
  • Fundamentals of Plotly.js
  • Creating basic charts with Plotly.js
  • Creating statistical charts with Plotly.js
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