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 Jupyter Notebooks to run Dash apps

With a change to imports and a minor change to app instantiation, we can easily start to run our apps within Jupyter Notebook environments. The package that makes this possible is jupyter_dash. Essentially, the difference is that we import the JupyterDash object (instead of importing Dash), and app instantiation occurs by calling this object, as follows:

from jupyter_dash import JupyterDash
app = JupyterDash(__name__)

One of the advantages of running apps in a notebook environment is that it is less tedious to make small changes, iterate them, and see results. Working with an IDE, the command line, and the browser, you need to constantly shift between them, while in a notebook environment, everything is in one place. This makes introducing simple changes and testing them easier. It can make your notebooks far more powerful and interesting as well.

The jupyter_dash package also provides an additional option while running the app, where...