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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

Customizing the histogram by modifying its bins and using multiple histograms

We can change the number of bins through the nbins parameter. We will first see the effect of using two extreme values for the number of bins. Setting nbins=2 generates the chart in Figure 8.2:

Figure 8.2 – A histogram of the Gini indicator with two bins

Figure 8.2 – A histogram of the Gini indicator with two bins

As you can see, the values were split into two equal bins, (20, 39.9) and (40, 59.9), and we can see how many countries are in each bin. It's quite simple and easy to understand, but not as nuanced as the histogram in Figure 8.1. On the other hand, setting nbins=500 produces the chart in Figure 8.3:

Figure 8.3 – A histogram of the Gini indicator with 500 bins

Figure 8.3 – A histogram of the Gini indicator with 500 bins

It is now much more detailed, maybe more detailed than useful. When you set too many bins, it is almost like looking at the raw data.

The default number of bins resulted in the bin size being intervals of five. Now...

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