Book Image

The Tableau Workshop

By : Sumit Gupta, Sylvester Pinto, Shweta Sankhe-Savale, JC Gillet, Kenneth Michael Cherven
Book Image

The Tableau Workshop

By: Sumit Gupta, Sylvester Pinto, Shweta Sankhe-Savale, JC Gillet, Kenneth Michael Cherven

Overview of this book

Learning Tableau has never been easier, thanks to this practical introduction to storytelling with data. The Tableau Workshop breaks down the analytical process into five steps: data preparation, data exploration, data analysis, interactivity, and distribution of dashboards. Each stage is addressed with a clear walkthrough of the key tools and techniques you'll need, as well as engaging real-world examples, meaningful data, and practical exercises to give you valuable hands-on experience. As you work through the book, you'll learn Tableau step by step, studying how to clean, shape, and combine data, as well as how to choose the most suitable charts for any given scenario. You'll load data from various sources and formats, perform data engineering to create new data that delivers deeper insights, and create interactive dashboards that engage end-users. All concepts are introduced with clear, simple explanations and demonstrated through realistic example scenarios. You'll simulate real-world data science projects with use cases such as traffic violations, urban populations, coffee store sales, and air travel delays. By the end of this Tableau book, you'll have the skills and knowledge to confidently present analytical results and make data-driven decisions.
Table of Contents (12 chapters)
Preface

Exploring Distribution for a Single Measure

Distribution charts such as histograms and box plots are used to show the distribution of continuous and numerical quantitative data. However, bar charts, as discussed in the previous chapter, are used when plotting discrete and categorical data. In these sections, you will focus on discrete and categorical chart types.

Creating a Histogram

A histogram represents frequency distribution. It shows the distribution of values and can help identify any outliers. Histograms take your continuous measures and splits the range of measurements. They are placed into buckets known as bins. Each bin is essentially a bar in a histogram representing the count of that range of values falling within that bin.

If you were to create a histogram of the salary of all the employees in a company, where the range of each bin is $10,000, your histogram would represent how many employees are earning $0-10,000, $10,001-20,000, $20,001-30,000, and so...