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Streamlit for Data Science

You're reading from   Streamlit for Data Science Create interactive data apps in Python

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Product type Paperback
Published in Sep 2023
Publisher Packt
ISBN-13 9781803248226
Length 300 pages
Edition 2nd 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 (15) Chapters Close

Preface 1. An Introduction to Streamlit FREE CHAPTER 2. Uploading, Downloading, and Manipulating Data 3. Data Visualization 4. Machine Learning and AI with Streamlit 5. Deploying Streamlit with Streamlit Community Cloud 6. Beautifying Streamlit Apps 7. Exploring Streamlit Components 8. Deploying Streamlit Apps with Hugging Face and Heroku 9. Connecting to Databases 10. Improving Job Applications with Streamlit 11. The Data Project – Prototyping Projects in Streamlit 12. Streamlit Power Users 13. Other Books You May Enjoy
14. Index

Beautifying Streamlit Apps

Welcome to Section 2 of the book! In Section 1, Creating Basic Streamlit Applications, we focused on the basics – visualization, deployment, and data munging – all the topics that are crucial to getting started with Streamlit. In this part of the book, the purpose is to explore Streamlit through more complex applications and use cases, with the intent of turning you into an expert Streamlit user.

Throughout this chapter, we’ll work with elements (including sidebars, tabs, columns, and colors) to extend our ability to make beautiful Streamlit applications. Along with this, we’ll explore how to create multi-page applications to manage user flow, creating a cleaner and more structured user experience.

By the end of this chapter, you should feel much more comfortable creating applications that are better than the average Minimum Viable Product (MVP). We’ll start by learning about columns and move on to the rest of...

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