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

Analyzing hypothetical survey costs using Streamlit for Teams

Imagine you are a data scientist for Big Internet Company (BIC). BIC sells budgeting software to users, and you are responsible for surveying the users of your app to see where the app could be improved. You work with a fairly typical team made up of a product manager, two software engineers, three project managers, two user experience researchers, and yourself, the lone data scientist. One day, your product manager messages you on Slack and asks you to figure out the right sample of users between the ages of 16 and 24, a crucial segment of the business, to take a 10-question survey about the software. In a brainstorming session, your researchers have found some evidence that giving people a 10% chance at winning a $500 gift card is more effective than giving people $50 for the response rates in your survey, and want you to incorporate that into your analysis. 

There are many factors that you need to consider here...