Tutorial of a Deployment of a Web app by Python and Streamlit for a Data Scientist

by Sho Akaba

An introduction to the deployment of a web app for data analysts.This book will be implemented in Python and Streamlit.Learn how a data scientist can easily and quickly deploy their analysis on a web app. We use Python for analysis and Streamlit for a web app. Streamlit is suitable for beginners because it can be implemented with less code than Django or Flask.In this book, we will introduce an example of making a Web application using linear regression analysis as an example. There are not 20 functions required for that.Please refer to the table of contents below for details on the required functions.Features of this book• For beginners• Be aware of simple explanations• All with sample code• Introducing data analysis as a web application as an example[Table of Contents]PrefaceAbout StreamlitCode NotationSetting up an Environment of StreamlitRun the python script by Setting up your environment using dockerIntroduction of basic functions Markdown notation (magic command) Data display st.titile() st.write() st.table() st.dataframe() st.latex() Graph display st.line_chart() st.area_chart() st.bar_chart() st.pyplot() Functions for Design st.checkbox() st.selectbox() st.multiselect() st.beta_columns() st.radio() st.number_input() st.sidebar.[element name]()Example of Web Linear regression on Boston house pricesExample of Web Principal Component Analysis(PCA)

109 pages, Kindle Edition

Published May 22, 2021