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Interactive Dashboards and Data Apps with Plotly and Dash

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

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Product type Paperback
Published in May 2021
Publisher Packt
ISBN-13 9781800568914
Length 364 pages
Edition 1st Edition
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Author (1):
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Elias Dabbas Elias Dabbas
Author Profile Icon Elias Dabbas
Elias Dabbas
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Table of Contents (18) Chapters Close

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

Creating an interactive KMeans clustering app

Let's now put everything together and make an interactive clustering application using our dataset. We will give users the option to choose the year, as well as the indicator(s) that they want. They can also select the number of clusters and get a visual representation of those clusters, in the form of a colored choropleth map, based on the discovered clusters.

Please note that it is challenging to interpret such results with multiple indicators because we will be handling more than one dimension. It can also be difficult if you are not an economist and don't know which indicators make sense to be checked with which other indicators, and so on.

The following screenshot shows what we will be working toward:

Figure 9.9 – An interactive KMeans clustering application

Figure 9.9 – An interactive KMeans clustering application

As you can see, this is a fairly rich application in terms of the combinations of options that it provides. As I also mentioned...

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