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

Summary

We introduced scatter plots and saw how to create them, both using the graph_objects module, and using Plotly Express. We saw how to create multiple traces and tried different approaches for that. We then discussed color mapping and setting and explored how different the process is for continuous and discrete (categorical) variables. We saw different scales – sequential, diverging, and qualitative. We also saw how we can set our own colors, sequences, and scales. We also tackled some issues that arise when we have outliers, and when we have over-plotting. We experimented with opacity, changing symbols, and marker sizes, as well as using logarithmic scales to make our charts more readable. We also introduced sliders and learned how they work, and created two sliders that work together to generate charts expressing three values (as opposed to two values previously). We then created a callback function that managed those interactions and integrated it into our app.

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