You're reading from Building Data-Driven Applications with Danfo.js A practical guide to data analysis and machine learning using JavaScript

Product type Paperback

Published in Sep 2021

Publisher Packt

ISBN-13 9781801070850

Length 476 pages

Edition 1st Edition

Languages

JavaScript

Tools

Danfo.js

Concepts

Data Analysis

Authors (2):

Stephen Oni

Rising Odegua

View More author details

Table of Contents (18) Chapters

Preface

1. Section 1: The Basics

2. Chapter 1: An Overview of Modern JavaScript FREE CHAPTER

3. Section 2: Data Analysis and Manipulation with Danfo.js and Dnotebook

4. Chapter 2: Dnotebook - An Interactive Computing Environment for JavaScript

5. Chapter 3: Getting Started with Danfo.js

6. Chapter 4: Data Analysis, Wrangling, and Transformation

7. Chapter 5: Data Visualization with Plotly.js

8. Chapter 6: Data Visualization with Danfo.js

9. Chapter 7: Data Aggregation and Group Operations

10. Section 3: Building Data-Driven Applications

11. Chapter 8: Creating a No-Code Data Analysis/Handling System

12. Chapter 9: Basics of Machine Learning

13. Chapter 10: Introduction to TensorFlow.js

14. Chapter 11: Building a Recommendation System with Danfo.js and TensorFlow.js

15. Chapter 12: Building a Twitter Analysis Dashboard

16. Chapter 13: Appendix: Essential JavaScript Concepts

17. Other Books You May Enjoy

Building the backend

In this section, we will be looking at how to create the following APIs for our app:

/api/tweet: This API is responsible for fetching a Twitter user and obtaining their data.
/api/nlp: This API is responsible for running sentiment analysis on the obtained user data.

These APIs will be consumed by the frontend components and will be used to create different visualizations and analyses. Let's start by creating the API to fetch a Twitter user's data.

Building the Twitter API

In this section, we will build an API that makes it easy to obtain tweets in which a Twitter user is mentioned. From each of the tweets, we will obtain their metadata, such as the text, the name of the sender, the numbers of likes and retweets, the device used to tweet, and the time the tweet was created.

To build the Twitter API for fetching a Twitter user's data and structure it to our taste for easy consumption in the frontend, we need to install a...