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

Collecting and cleaning data

There are two ways in which to get data from Goodreads: through their Application Programming Interface (API), which allows developers to programmatically access data about books, and through their manual exporting function. Sadly, Goodreads is deprecating their API in the near future and, as of December 2020, are not giving access to more developers.

The original Goodreads app uses the API, but our version will rely on the manual exporting function that the Goodreads website has instead. To get your data, head over to and download your own data. If you do not have a Goodreads account, feel free to use my personal data for this, which can be found at I have saved my Goodreads data in a file, called goodreads_history.csv, in a new folder, called streamlit_goodreads_book. To make your own folder with the appropriate setup, run the following in your Terminal...