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Getting Started with Streamlit for Data Science

You're reading from   Getting Started with Streamlit for Data Science Create and deploy Streamlit web applications from scratch in Python

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Product type Paperback
Published in Aug 2021
Publisher Packt
ISBN-13 9781800565500
Length 282 pages
Edition 1st Edition
Languages
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Author (1):
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Tyler Richards Tyler Richards
Author Profile Icon Tyler Richards
Tyler Richards
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Table of Contents (17) Chapters Close

Preface 1. Section 1: Creating Basic Streamlit Applications
2. Chapter 1: An Introduction to Streamlit FREE CHAPTER 3. Chapter 2: Uploading, Downloading, and Manipulating Data 4. Chapter 3: Data Visualization 5. Chapter 4: Using Machine Learning with Streamlit 6. Chapter 5: Deploying Streamlit with Streamlit Sharing 7. Section 2: Advanced Streamlit Applications
8. Chapter 6: Beautifying Streamlit Apps 9. Chapter 7: Exploring Streamlit Components 10. Chapter 8: Deploying Streamlit Apps with Heroku and AWS 11. Section 3: Streamlit Use Cases
12. Chapter 9: Improving Job Applications with Streamlit 13. Chapter 10: The Data Project – Prototyping Projects in Streamlit 14. Chapter 11: Using Streamlit for Teams 15. Chapter 12: Streamlit Power Users 16. Other Books You May Enjoy

Chapter 7: Exploring Streamlit Components

Streamlit has a full-time team of developers working on new features but also thrives because it is open to community-driven development. Undoubtedly, there will be community members who want a specific feature that did not make it onto the roadmap of priorities. Streamlit Components allow them the flexibility to go out and make it themselves, and immediately use their idea in their own Streamlit apps.

Our priority in this chapter is to learn how to find and use community-made Streamlit Components. For that, we will run through three excellent Streamlit apps, one to learn how to embed code into our Streamlit apps, another for adding beautiful animations to them, and a third to embed easy automated exploratory data analysis (EDA) to Streamlit apps.

In this chapter, we will cover the following topics:

  • Using Streamlit Components: streamlit-embedcode
  • Using Streamlit Components: streamlit-lottie
  • Using Streamlit Components...
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