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

Technical requirements

We will be exploring a few options from sklearn, as well as NumPy. Otherwise, we will be using the same tools we have been using. For visualization and building interactivity, Dash, JupyterDash, the Dash Core Component library, Dash HTML Components, Dash Bootstrap Components, Plotly, and Plotly Express will be used. For data manipulation and preparation, we will use pandas and NumPy. JupyterLab will be used for exploring and building independent functionality. Finally, sklearn will be used for building our machine learning models, as well as for preparing our data.

The code files of this chapter can be found on GitHub at https://github.com/PacktPublishing/Interactive-Dashboards-and-Data-Apps-with-Plotly-and-Dash/tree/master/chapter_09.

Check out the following video to see the Code in Action at https://bit.ly/3x8PAmt.