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 an interactive map into our app

The map that we created, together with the Dropdown and Markdown components, can become the first exploratory tool in our app. We can remove the population bar chart now, and in its place, we can place the components we just created, for users to explore all the indicators, see them on the map, and scroll through the years, and for each indicator, get the full details, as well as seeing the limitations and potential issues. Once something catches the user's eye, they can then find another chart that gives more detail about the indicator they want if it exists.

In order to fully incorporate the new functionality into our app, we need to go through the following steps:

  1. Add the definition of series at the top of the app.py module:
    series = pd.read_csv('data/PovStatsSeries.csv')
  2. Add the definition of the multiline_indicator function, anywhere before app.layout:
    def multiline_indicator(indicator):
       ...