You're reading from Interactive Dashboards and Data Apps with Plotly and Dash Harness the power of a fully fledged frontend web framework in Python – no JavaScript required

Product type Paperback

Published in May 2021

Publisher Packt

ISBN-13 9781800568914

Length 364 pages

Edition 1st Edition

Languages

JavaScript

Tools

Dash

Concepts

Data Visualization

Author (1):

Elias Dabbas

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Table of Contents (18) Chapters

Preface

1. Section 1: Building a Dash App

2. Chapter 1: Overview of the Dash Ecosystem FREE CHAPTER

3. Chapter 2: Exploring the Structure of a Dash App

4. Chapter 3: Working with Plotly's Figure Objects

5. Chapter 4: Data Manipulation and Preparation, Paving the Way to Plotly Express

6. Section 2: Adding Functionality to Your App with Real Data

7. Chapter 5: Interactively Comparing Values with Bar Charts and Dropdown Menus

8. Chapter 6: Exploring Variables with Scatter Plots and Filtering Subsets with Sliders

9. Chapter 7: Exploring Map Plots and Enriching Your Dashboards with Markdown

10. Chapter 8: Calculating the Frequency of Your Data with Histograms and Building Interactive Tables

11. Section 3: Taking Your App to the Next Level

12. Chapter 9: Letting Your Data Speak for Itself with Machine Learning

13. Chapter 10: Turbo-charge Your Apps with Advanced Callbacks

14. Chapter 11: URLs and Multi-Page Apps

15. Chapter 12: Deploying Your App

16. Chapter 13: Next Steps

17. Other Books You May Enjoy

Establishing the general development, deployment, and update workflow

When we discuss deployment, we are assuming that we are happy enough with what we have developed so far. This could be when we run our app for the first time, or after having introduced some changes or fixed some bugs. So, our data and code are ready to go. Our focus will be to set up the required infrastructure to enable us to run the code online.

The setup we will be going through is going to be simple and straightforward. We will be using Linode as an example for our hosting provider. An important feature of Linode is that it follows a philosophy of "open cloud." This means that the server we will be working with will be a plain Linux server, using open source components and packages that you can customize the way you want and migrate to and from with ease. The potential challenge here is that with more freedom comes more complexity and responsibility. In Chapter 4, Data Manipulation and Preparation...