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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

Summary

In this chapter, we covered plotting and visualization with Danfo.js. First, we showed you how to set up Danfo.js and Plotly in a new project, and then moved on to downloading a dataset, which we loaded into a DataFrame. Next, we showed you how to create basic charts such as line, bar, and scatter plots, and then statistical charts such as histograms and box and violin plots. Finally, we showed you how to configure plots created with Danfo.js.

The knowledge you have gained in this and Chapter 5, Data Visualization with Plotly.js, will be of practical use when creating data-driven apps as well as custom dashboards.

In the next chapter, you'll learn about data aggregation and group-by operations, thereby understanding how to perform data transformations such as merging, joining, and concatenation.

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