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

Introducing sliders and range sliders

The Slider and RangeSlider components are basically circles that users can drag horizontally or vertically to set or change a certain value. They are typically used for setting continuous values, as their appearance and dragging functionality are a natural fit for that. But this is not a requirement as we can use them for categorical/discrete values as well. We have seen that we have three levels of our perc_pov_ metrics, and we know that we have all the years in our dataset to choose from. We now want to create two sliders. One allows users to select the level of poverty that they want to analyze, and the other allows them to select the year. Each combination of selections will create a different subset, and result in a different chart. Figure 6.21 shows the top part of the end result that we will be working toward:

Figure 6.21 – Two sliders controlling a chart

Figure 6.21 – Two sliders controlling a chart

As you can see, the new functionality requires...