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

Summary

We first introduced the optional State argument to callback function decorators. We saw how by combining it with Input, we can defer the execution of functions until the user decides to execute them. We also ran several examples that added buttons to invoke the execution. We then created a simple app where the user's inputs to a certain component were used to dynamically populate options of another component that was "waiting." Those new options were in turn used to create another component.

Another interesting application of simple principles was allowing users to add new components having dynamic content.

We finally introduced the most powerful and flexible feature, the pattern-matching callbacks. We created an app where users are able to add as many charts as they want. Furthermore, those charts acted independently from one another, and users were empowered to customize their own dashboard.

That was a lot to cover, and we turn next to another feature...