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Interactive Dashboards and Data Apps with Plotly and Dash

Interactive Dashboards and Data Apps with Plotly and Dash

By : Dabbas
4.4 (24)
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Interactive Dashboards and Data Apps with Plotly and Dash

Interactive Dashboards and Data Apps with Plotly and Dash

4.4 (24)
By: Dabbas

Overview of this book

Plotly's Dash framework is a life-saver for Python developers who want to develop complete data apps and interactive dashboards without JavaScript, but you'll need to have the right guide to make sure you’re getting the most of it. With the help of this book, you'll be able to explore the functionalities of Dash for visualizing data in different ways. Interactive Dashboards and Data Apps with Plotly and Dash will first give you an overview of the Dash ecosystem, its main packages, and the third-party packages crucial for structuring and building different parts of your apps. You'll learn how to create a basic Dash app and add different features to it. Next, you’ll integrate controls such as dropdowns, checkboxes, sliders, date pickers, and more in the app and then link them to charts and other outputs. Depending on the data you are visualizing, you'll also add several types of charts, including scatter plots, line plots, bar charts, histograms, and maps, as well as explore the options available for customizing them. By the end of this book, you'll have developed the skills you need to create and deploy an interactive dashboard, handle complexities and code refactoring, and understand the process of improving your application.
Table of Contents (18 chapters)
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1
Section 1: Building a Dash App
6
Section 2: Adding Functionality to Your App with Real Data
11
Section 3: Taking Your App to the Next Level

Plotting bar charts vertically and horizontally

The default display of bar charts is vertical. This is intuitive and easy to understand. Each category or item takes a separate position on the x axis, and the heights of the bars represent a certain quantity on the y axis. The same applies when the bars are displayed horizontally, only in this case, the width of the bars is what represents the quantity. Usually, with relatively fewer values, the vertical orientation is good. However, horizontal orientation can be more effective in two cases:

  • When we have many categories: In this case, the bars might not fit on the screen, and we might need to either make them much thinner than the default width, or we might need to force horizontal scrolling, which is not as natural as vertical scrolling.
  • When the names of the categories are relatively long: This is not really a big problem, and the solution is easy. Plotly already handles this for us, by automatically changing the angle...

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