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

Chapter 10: Turbo-charge Your Apps with Advanced Callbacks

We will now take our apps to a new level of abstraction and power by introducing new options available to callbacks. The general pattern we have followed has been that we provide users with a component that they can interact with. Based on a given set of options available to the component, users can influence certain actions, such as producing a chart, for example. We will be exploring other options such as deferring the execution of callbacks until a certain event happens, for example, clicking a "Submit" button. We will also take a look at how we can allow users to modify the layout of the app itself, by allowing them to add new dynamic components to it. We will use some of this knowledge to add a minor but important improvement to the clustering functionality that we introduced in Chapter 9, Letting Your Data Speak for Itself with Machine Learning.

We will first start by introducing the optional State parameter...