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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

Adding HTML and other components to the app

From now until the end of this chapter, we will mainly be focusing on the app.layout attribute of our app and making changes to it. It's straightforward to do so; we simply add elements to the top-level html.Div element's list (the children parameter):

html.Div(children=[component_1, component_2, component_3, …])

Adding HTML components to a Dash app

Since the available components in the package correspond to actual HTML tags, it is the most stable package. Let's quickly explore the parameters that are common to all its components.

At the time of this writing, Dash HTML Components has 131 components, and there are 20 parameters that are common to all of them.

Let's go over some of the most important ones that we will frequently be using:

  • children: This is typically the main (and first) container of the content of the component. It can take a list of items, or a single item.
  • className: This is the same as the class attribute, only renamed as such.
  • id: While we won't be covering this parameter in this chapter, it is the crucial one in making interactivity work, and we will be using it extensively while building the app. For now, it's enough to know that you can set arbitrary IDs to your components so you can identify them and later use them for managing interactivity.
  • style: This is similar to the HTML attribute of the same name, but with a few differences. First, its attributes are set using camelCase. So, say you wanted to set the following attributes in Dash HTML Components:
    <h1 style="color:blue; font-size: 40px; margin-left: 20%">A Blue Heading</h1>

    You would specify them this way:

    import dash_html_components as html
    html.H1(children='A Blue Heading',
            style={'color': 'blue',
                   'fontSize': '40px',
                   'marginLeft': '20%'})

    As you have most likely noticed, the style attribute is set using a Python dictionary.

The other parameters have different uses and rules, depending on the respective component that they belong to. Let's now practice adding a few HTML elements to our app. Going back to the same app.py file, let's experiment with adding a few more HTML elements and run the app one more time, as we just did. I kept the top and bottom parts the same, and I mainly edited app.layout:

…
app = dash.Dash(__name__)
app.layout = html.Div([
    html.H1('Poverty And Equity Database',
            style={'color': 'blue',
                   'fontSize': '40px'}),
    html.H2('The World Bank'),
    html.P('Key Facts:'),
    html.Ul([
        html.Li('Number of Economies: 170'),
        html.Li('Temporal Coverage: 1974 - 2019'),
        html.Li('Update Frequency: Quarterly'),
        html.Li('Last Updated: March 18, 2020'),
        html.Li([
            'Source: ',
          html.A('https://datacatalog.worldbank.org/dataset/poverty-and-equity-database',         href='https://datacatalog.worldbank.org/dataset/poverty-and-equity-database')
        ])
    ])
])
…
python app.py

That should produce the following screen:

Figure 1.5 – Updated app rendered in the browser

Figure 1.5 – Updated app rendered in the browser

Tip

If you are familiar with HTML, this should look straightforward. If not, please check out a basic tutorial online. A great source to start would be W3Schools: https://www.w3schools.com/html/.

In the updated part, we just added a <p> element and an unordered list, <ul>, within which we added a few list items, <li> (using a Python list), the last of which contained a link using the <a> element.

Note that since these components are implemented as Python classes, they follow Python's conventions of capitalizing class names: html.P, html.Ul, html.Li, html.A, and so on.

Feel free to experiment with other options: adding new HTML components, changing the order, trying to set other attributes, and so on.

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Interactive Dashboards and Data Apps with Plotly and Dash
Published in: May 2021
Publisher: Packt
ISBN-13: 9781800568914
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