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

Getting to know the data attribute

First, we start by adding a scatter plot using a very small and simple dataset. Later in the chapter, we will use our poverty dataset to create other plots. Once you have created your Figure object and assigned it to a variable, you have access to a large number of convenient methods for manipulating that object. The methods related to adding data traces all start with add_, followed by the type of chart we are adding, for example, add_scatter or add_bar.

Let's go through the full process of creating a scatter plot:

  1. Import the graph_objects module:
    import plotly.graph_objects as go
  2. Create an instance of a Figure object and assign it to a variable:
    fig = go.Figure()
  3. Add a scatter trace. The minimum parameters required for this type of chart are two arrays for the x and y values. These can be provided as lists, tuples, NumPy arrays, or pandas Series:
    fig.add_scatter(x=[1, 2, 3], y=[4, 2, 3])
  4. Display the resulting figure. You...