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

Incorporating the function into the app

Here is the plan for the functionality that we are going to introduce:

  1. Create a drop-down list using the countries and regions available in our dataset.
  2. Create a callback function that takes the selected country, filters the dataset, and finds the population of that country in the year 2010.
  3. Return a small report about the found data. Figure 2.7 shows the desired end result:
    Figure 2.7 – A drop-down list used to display the selected country's population

Figure 2.7 – A drop-down list used to display the selected country's population

Important note

Now that we are beginning to use our dataset, we will start opening files from the data folder. This assumes that the app you are running is in the same folder. The code for each chapter in the GitHub repository is placed in its own folder for easy access; however, the code only works if the data folder and app.py are both in the same folder.

Figure 2.8 shows what this folder structure might look like:

Figure 2.8 – The assumed folder structure for the app

Figure...