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Learn Python by Building Data Science Applications

You're reading from   Learn Python by Building Data Science Applications A fun, project-based guide to learning Python 3 while building real-world apps

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Product type Paperback
Published in Aug 2019
Publisher Packt
ISBN-13 9781789535365
Length 482 pages
Edition 1st Edition
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Authors (2):
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Philipp Kats Philipp Kats
Author Profile Icon Philipp Kats
Philipp Kats
David Katz David Katz
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David Katz
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Table of Contents (26) Chapters Close

Preface 1. Section 1: Getting Started with Python
2. Preparing the Workspace FREE CHAPTER 3. First Steps in Coding - Variables and Data Types 4. Functions 5. Data Structures 6. Loops and Other Compound Statements 7. First Script – Geocoding with Web APIs 8. Scraping Data from the Web with Beautiful Soup 4 9. Simulation with Classes and Inheritance 10. Shell, Git, Conda, and More – at Your Command 11. Section 2: Hands-On with Data
12. Python for Data Applications 13. Data Cleaning and Manipulation 14. Data Exploration and Visualization 15. Training a Machine Learning Model 16. Improving Your Model – Pipelines and Experiments 17. Section 3: Moving to Production
18. Packaging and Testing with Poetry and PyTest 19. Data Pipelines with Luigi 20. Let's Build a Dashboard 21. Serving Models with a RESTful API 22. Serverless API Using Chalice 23. Best Practices and Python Performance 24. Assessments 25. Other Books You May Enjoy

Let's Build a Dashboard

In the previous chapter, we learned how to create robust pipelines and schedule them so that we have metrics updated every day. With that, our valuable data product is automated! What should we do? Perhaps it is a good moment to discuss dashboards. Dashboards are essentially the entry point for you to monitor the behavior of the system (your service, markets, users, or anything else) via a set of data visualizations. Dashboards help teams and companies to ensure the business is running smoothly or to detect—and adjust tochanges or anomalies. So, to help us understand them better, let's see how they work.

The following topics will be covered in this chapter:

  • Different ways to build a dashboard
  • Building a static dashboard
  • Building and serving a dynamic dashboard
  • Pros and cons of different approaches
  • Debugging Altair
...
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