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)

Dataset

We will be working with trading data on commodities in this chapter. The Federal Reserve Bank of St Louis, United States, compiles data on commodities. Datasets are available on http://fred.stlouisfed.org. You can obtain time series data on import values and import volumes of commodities traded by the United States. We will download data on bananas, olive oil, sugar, uranium, cotton, oranges, wheat, aluminium, iron, and corn.

Inside the chapter directory of the GitHub repository, you will find the generate_dataset.ipynb Jupyter Notebook. Just run the Notebook to download, transform, and generate the two CSV files we will upload. If you want to skip running the Notebook, the two CSV files, fsb_st_louis_commodities.csv and usda_oranges_and_bananas_data.csv, are also present in the repository, ready for upload.

The FSB data on commodity prices in fsb_st_louis_commodities...