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

Using facets to split charts into multiple sub-charts – horizontally, vertically, or wrapped

This is a very powerful technique that allows us to add a new dimension to our analysis. We can select any feature (column) from our dataset to split the chart by. If you are expecting a long explanation of how it works, and what you need to learn to master it, don't. Just like most other things in Plotly Express, if you have a long-form (tidy) dataset, all you have to do is select a column and use its name for the facet_col or facet_row parameter. That's it.

Let's take a quick look at the available options for facets by looking at the relevant facet parameters:

  • facet_col: This means you want to split the chart into columns, and the selected column name will be used to split them. This results in the charts being displayed side by side (as columns).
  • facet_row: Similarly, if you want to split the chart into rows, you can use this parameter, which will split...