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

Summary

We started by focusing on the importance of basic skills in handling data. We emphasized the importance of mastering data manipulation and cleaning skills, which will allow you to format your data into the shape that you want and make it easy to analyze and visualize. We also mentioned various data visualization techniques and types of charts that can be explored to increase your fluency in expressing ideas visually.

We also discussed the other Dash components that we didn't cover in the book, as well as the community components that are constantly being developed. Eventually, you might decide to develop your own set of components and contribute additional functionality to the Dash ecosystem, and I look forward to pip install dash-your-components!

We then discussed exploring machine learning and how we can make our models visual and interactive. Establishing data manipulation, visualization, and interactivity skills will help you a lot in making your models interpretable...