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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

Connecting to Databases

In the previous chapters we focused entirely on data stored in individual files, but most of the real-world, work-based applications center around data stored in databases. Companies tend to store their data in the cloud, and therefore, being able to perform analyses on this data is a critical skill. In this chapter, we will explore how to access and use data stored in popular databases such as Snowflake and BigQuery. For each database, we’ll connect to the database, write SQL queries, and then make an example app.

Whether you are looking to perform ad hoc analysis on large datasets or build data-driven applications, the ability to efficiently retrieve and manipulate data from databases is essential. By the end of this chapter, you will have a strong understanding of how to use Streamlit to connect to and interact with databases, empowering you to extract insights and make data-driven decisions with confidence.

In this chapter, we will cover...

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