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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
Toc

Table of Contents (18) Chapters close

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

Expanding your data manipulation and preparation skills

If you have read any introductory text on data science, you will have probably been told that data scientists spend the majority of their time cleaning data, reformatting it, and reshaping it.

As you have read this book, you will have probably seen this in action!

We saw several times how much code and mental effort, and importantly, domain knowledge, goes into just getting our data into a certain format. Once we have our data in a standardized format, for example, a long form (tidy) DataFrame, then our lives become easier.

You might want to learn more pandas and NumPy for a more complete set of techniques on reshaping your data however you want. As mentioned at the beginning of the chapter, learning new pandas techniques without a practical purpose in mind can help a lot in expanding your imagination. Learning regular expressions can help a lot in text analysis, because text is typically unstructured, and finding and...

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