Book Image

Apache Superset Quick Start Guide

By : Shashank Shekhar
Book Image

Apache Superset Quick Start Guide

By: Shashank Shekhar

Overview of this book

Apache Superset is a modern, open source, enterprise-ready business intelligence (BI) web application. With the help of this book, you will see how Superset integrates with popular databases like Postgres, Google BigQuery, Snowflake, and MySQL. You will learn to create real time data visualizations and dashboards on modern web browsers for your organization using Superset. First, we look at the fundamentals of Superset, and then get it up and running. You'll go through the requisite installation, configuration, and deployment. Then, we will discuss different columnar data types, analytics, and the visualizations available. You'll also see the security tools available to the administrator to keep your data safe. You will learn how to visualize relationships as graphs instead of coordinates on plain orthogonal axes. This will help you when you upload your own entity relationship dataset and analyze the dataset in new, different ways. You will also see how to analyze geographical regions by working with location data. Finally, we cover a set of tutorials on dashboard designs frequently used by analysts, business intelligence professionals, and developers.
Table of Contents (10 chapters)


In this chapter, we will make use of two datasets. First, we will download the global list of airports as of 2017. We will download it from the OpenFlights website. They have multiple datasets—airports, airlines, routes, and aeroplanes in use. These are available on their data page at:

This is how it should appear:

We will fetch the airports dataset from the following GitHub link: Some changes have to be made before uploading it. In the Chapter07 directory for the GitHub repository, you will find the generate_dataset.ipynb Jupyter Notebook. Run it to create the two datasets.

This is the code for creating the airports_modified.csv file: