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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 2. Uploading, Downloading, and Manipulating Data FREE CHAPTER 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

Technical requirements

The following is a list of software and hardware installations that are required for this chapter:

  • streamlit-lottie: We already installed this library in our Components chapter, but if you have yet to install it, now is a great time! To download this library, run the following code in your Terminal:
    pip install streamlit-lottie
    

    Interestingly, streamlit-lottie uses the lottie open-source library, which allows us to add web-native animations (such as a GIF) to our Streamlit apps. Frankly, it is a wonderful library that you can use to beautify Streamlit apps and was created by Fanilo Andrianasolo, a prolific Streamlit app creator.

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