Book Image

Getting Started with Streamlit for Data Science

By : Tyler Richards
Book Image

Getting Started with Streamlit for Data Science

By: Tyler Richards

Overview of this book

Streamlit shortens the development time for the creation of data-focused web applications, allowing data scientists to create web app prototypes using Python in hours instead of days. Getting Started with Streamlit for Data Science takes a hands-on approach to helping you learn the tips and tricks that will have you up and running with Streamlit in no time. You'll start with the fundamentals of Streamlit by creating a basic app and gradually build on the foundation by producing high-quality graphics with data visualization and testing machine learning models. As you advance through the chapters, you’ll walk through practical examples of both personal data projects and work-related data-focused web applications, and get to grips with more challenging topics such as using Streamlit Components, beautifying your apps, and quick deployment of your new apps. By the end of this book, you’ll be able to create dynamic web apps in Streamlit quickly and effortlessly using the power of Python.
Table of Contents (17 chapters)
Section 1: Creating Basic Streamlit Applications
Section 2: Advanced Streamlit Applications
Section 3: Streamlit Use Cases


What a fun chapter! We have learned so much here – from how to come up with data science projects of our own to how to create initial MVPs, to the iterative improvement of our apps. We have done this all through the lens of our Goodreads dataset, and we have taken this app from just an idea to a fully functioning app hosted on Streamlit Sharing. I look forward to seeing all the different types of Streamlit apps that you create. Please create something fun and send it to me on Twitter at @tylerjrichards. In the next chapter, we will focus on learning how to use Streamlit at work with the new Streamlit product, Streamlit for Teams. See you there!