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

Allowing users to add dynamic components to the app

Not only will users be able to add components to the app's layout, but the components' contents will also be dynamically generated. Take a look at Figure 10.6 for the simplest example that we will start with:

Figure 10.6 – An app allowing users to add components to the app's layout

Figure 10.6 – An app allowing users to add components to the app's layout

Although extremely simple, the charts in this app have different dynamic names, as you can see in the chart titles. This was based on the dynamic value of n_clicks, which changes on every click.

The amount of code required to generate this is similar to any simple app; there isn't much complexity involved. We just need to look at it with fresh eyes. Let's start by coding the layout, which will consist of two simple components:

  1. Create a button to trigger the addition of new charts:
    dbc.Button("Add Chart", id='button')
  2. Create an empty div, with its children attribute...