Book Image

Interactive Dashboards and Data Apps with Plotly and Dash

By : Elias Dabbas
Book Image

Interactive Dashboards and Data Apps with Plotly and Dash

By: Elias Dabbas

Overview of this book

Plotly's Dash framework is a life-saver for Python developers who want to develop complete data apps and interactive dashboards without JavaScript, but you'll need to have the right guide to make sure you’re getting the most of it. With the help of this book, you'll be able to explore the functionalities of Dash for visualizing data in different ways. Interactive Dashboards and Data Apps with Plotly and Dash will first give you an overview of the Dash ecosystem, its main packages, and the third-party packages crucial for structuring and building different parts of your apps. You'll learn how to create a basic Dash app and add different features to it. Next, you’ll integrate controls such as dropdowns, checkboxes, sliders, date pickers, and more in the app and then link them to charts and other outputs. Depending on the data you are visualizing, you'll also add several types of charts, including scatter plots, line plots, bar charts, histograms, and maps, as well as explore the options available for customizing them. By the end of this book, you'll have developed the skills you need to create and deploy an interactive dashboard, handle complexities and code refactoring, and understand the process of improving your application.
Table of Contents (18 chapters)
1
Section 1: Building a Dash App
6
Section 2: Adding Functionality to Your App with Real Data
11
Section 3: Taking Your App to the Next Level

What we have covered so far

In the first part of the book, we covered the basics of Dash apps. We first explored how they are structured and how to manage the visual elements. Then, we explored how interactivity is created, which is mainly by using callback functions. This allowed us to create fully interactive apps. We then explored the structure of the Figure object and learned how to modify and manipulate it to generate the charts we desire. After that, we saw how important data manipulation and preparation are for data visualization. We went through a reshaping of our dataset, to make things more intuitive to work with. This paved the way for easily learning and using Plotly Express.

Part 2 was about getting thoroughly familiar with several types of charts, as well as interactive components. We implemented all the knowledge we built in Part 1, but most importantly, we did this in a practical setting. We gradually added more and more charts, components, and functionality to one...