Learn end-to-end features of Streamlit to build Data apps for Analytics- Data Engineering, Data Science
Welcome to “Building Data Apps with Streamlit”! In this comprehensive course, you will learn how to leverage the power of Streamlit to build interactive and user-friendly data applications.
What you’ll learn
- Learn the basic and some advanced features of Streamlit.
- Hands-on streamlit features to build UI widgets.
- How to build Data apps/Web apps for Data Science and Data Analytics applications.
- How to deploy Streamlit data app from GitHub to community cloud for Free.
- Overview of Data Apps for analytics.
Course Content
- Introduction –> 3 lectures • 9min.
- Displaying text/messages in Streamlit –> 1 lecture • 31min.
- Displaying Data on the App –> 3 lectures • 31min.
- Input Widgets –> 8 lectures • 1hr 58min.
- Visualizations and Chart in Streamlit –> 4 lectures • 38min.
- Layout and Containers in Streamlit –> 7 lectures • 48min.
- Status Element –> 2 lectures • 19min.
- Advanced Concepts –> 6 lectures • 58min.
- Control Flow in Streamlit –> 3 lectures • 21min.
- Deploy and share streamlit App using Cloud –> 2 lectures • 7min.
- Project: Build and Deploy Work Order Management App –> 3 lectures • 1hr 41min.
Requirements
Welcome to “Building Data Apps with Streamlit”! In this comprehensive course, you will learn how to leverage the power of Streamlit to build interactive and user-friendly data applications.
Streamlit is a Python library that allows you to quickly and easily create web-based data apps with just a few lines of code. It simplifies the process of building interactive dashboards, visualizations, and data exploration tools, making it an ideal choice for data scientists, analysts, and developers.
Here’s a breakdown of the main topics covered in the course:
1. Introduction
- Welcome to the course
- What is Streamlit and Why Learn Streamlit
- Getting started and Installation
2. Displaying text/messages in Streamlit
- Different ways to display text on the app- markdown, title, header, sub-header, help text, LaTex
3. Displaying Data on the App
- Different ways to display data, tabular data in streamlit
- How to display/format dataframe using streamlit
- How to display Metrics/KPIs and static table in Stream
4. Input Widgets
- Widgets in Streamlit
- Button, Download-button and Checkbox
- Radio Button
- Select box
- Multi values selection, Sliding bar
- Text input( widget to input single text line)
- Widgets to input number, Date and Time
- Text Area to input larger text, File upload
5. Visualizations and Chart in Streamlit
- Introduction
- Line chart, Bar chart, Area chart and Pyplot
- Altair chart, Plotly, Bokeh Interactive Chart
- Pydeck and Map using streamlit
6. Layout and Containers in Streamlit
- Introduction
- Sidebar
- Columns
- Multi Tabs layout
- Expander
- Container
- Empty
7. Status Element
- Introduction to status widgets
- Widgets for status messages-warning, error, success, exceptions, waiting
8. Control Flow in Streamlit
- Introduction
- How to halt the processing of the App using Control flow
- Form and Form Submit button
9 Advanced Concepts
9.1 Caching in Streamlit
- Introduction to Caching in streamlit
- How to improve the app’s performance using Caching
9.2 Session State
- Introduction
- How to use session state to populate widget
9.3 Theming and Page Configuration
- Introduction
- How to configure Theme and Page in Streamlit App
10. Deploy and share streamlit App using Cloud
- Introduction to streamlit community cloud
- Integrate GitHub to community cloud and deploy app
11. Project: Build and Deploy Work Order Management App
- Introduction to Work Order Management App
- High level design and Pseudocode
- Development and Deployment of the App
12. Congratulations and Bonus chapter