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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

Using facets to split charts into multiple sub-charts – horizontally, vertically, or wrapped

This is a very powerful technique that allows us to add a new dimension to our analysis. We can select any feature (column) from our dataset to split the chart by. If you are expecting a long explanation of how it works, and what you need to learn to master it, don't. Just like most other things in Plotly Express, if you have a long-form (tidy) dataset, all you have to do is select a column and use its name for the facet_col or facet_row parameter. That's it.

Let's take a quick look at the available options for facets by looking at the relevant facet parameters:

  • facet_col: This means you want to split the chart into columns, and the selected column name will be used to split them. This results in the charts being displayed side by side (as columns).
  • facet_row: Similarly, if you want to split the chart into rows, you can use this parameter, which will split...
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