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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

Product type Book
Published in May 2021
Publisher Packt
ISBN-13 9781800568914
Pages 364 pages
Edition 1st Edition
Languages
Author (1):
Elias Dabbas Elias Dabbas
Profile icon Elias Dabbas

Table of Contents (18) Chapters

Preface 1. Section 1: Building a Dash App
2. Chapter 1: Overview of the Dash Ecosystem 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

Getting to know the data attribute

First, we start by adding a scatter plot using a very small and simple dataset. Later in the chapter, we will use our poverty dataset to create other plots. Once you have created your Figure object and assigned it to a variable, you have access to a large number of convenient methods for manipulating that object. The methods related to adding data traces all start with add_, followed by the type of chart we are adding, for example, add_scatter or add_bar.

Let's go through the full process of creating a scatter plot:

  1. Import the graph_objects module:
    import plotly.graph_objects as go
  2. Create an instance of a Figure object and assign it to a variable:
    fig = go.Figure()
  3. Add a scatter trace. The minimum parameters required for this type of chart are two arrays for the x and y values. These can be provided as lists, tuples, NumPy arrays, or pandas Series:
    fig.add_scatter(x=[1, 2, 3], y=[4, 2, 3])
  4. Display the resulting figure. You...
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