Book Image

Building Data-Driven Applications with Danfo.js

By : Rising Odegua, Stephen Oni
Book Image

Building Data-Driven Applications with Danfo.js

By: Rising Odegua, Stephen 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)
1
Section 1: The Basics
3
Section 2: Data Analysis and Manipulation with Danfo.js and Dnotebook
10
Section 3: Building Data-Driven Applications

Introduction to Dnotebook

Over the past few years in the field of data science, interactive computing environments such as Jupyter Notebook and JupyterLab have actually made a huge impact in terms of how code is shared, and this has enhanced fast and rapid iterations of ideas.

In recent times, data science is moving towards the browser side, in order to support diverse users such as web developers. This means that a lot of mature data science tooling available in the Python ecosystem needed to be ported or made available in JavaScript as well. Following this line of reasoning, we, the authors of this book, as well as the creators of Danfo.js, decided to create a new version of the Jupyter Notebook specifically targeted at the JavaScript ecosystem.

Dnotebook, as we have called it, helps you to perform quick and interactive experimentation/prototyping in JavaScript. That means you can write code and view the results instantly in an interactive and notebook-like manner as seen in...