Build Awesome Web Apps and Dashboards with Python - Full Shiny for Python Course
Offered By: Keith Galli via YouTube
Course Description
Overview
Syllabus
- About Shiny for Python & Course Overview
- Intro to Shiny & Gallery Examples
- Getting Started with the Shinylive Playground
- Building a custom visualization with Shinylive
- Easily sharing the code/application for a Shinylive app
- Building a Shiny Express App locally VSCode
- How to run app if you're not using VSCode
- Further customization of our app adding title, using CSV data, dynamic input
- Deploying our Shiny app to the web
- Part 2 Overview
- Getting Started with Code Part 2
- Adding Shiny Components Inputs, Outputs, & Display Messages
- Creating an Additional Visualization Sales Over Time by City
- What are Reactive.Calcs and How Do We Use Them Properly? DataFrame Best Practices
- Creating an Additional Visualization Sales Over Time by City — Continued
- Filtering City Data with Select Inputs UI.Input_Selectize
- Rendering Shiny Inputs Within Text
- Quick Formatting Adjustments
- Understanding the Shiny Reactivity Model How Does Shiny Render Things?
- Adding a Checkbox Input to Change Out Bar Chart Marker Colors
- Deploying Our Updated App!
- Advanced Concepts in Shiny Reactivity Reactive.Effect, Reactive.Event, Reactive.Isolate, Reactive.Invalidate_Later & Other Resources
- Thank you to Posit Connect, Our Sponsor
- Part 3 Overview
- Using Shiny Templates to Get Started Fast
- Using Layout Components to Customize our Apps Cards, Sidebars, Tabs, etc.
- Adding a Sidebar within a Card
- Adding a Card with Tabs to Display Various Visualizations
- Structuring Data in Columns / Grids layout_columns & layout_column_wrap
- Final Touches & Tips Filling in Visualizations into our Tab Views
- Part 4 Overview
- Getting Setup with the Code cloning branch from GitHub
- Adding Matplotlib-based visualizations render.plot Shiny for Python decorator
- Create a Seaborn Heatmap Chart Sales Volume by Hour of the Day
- Creating Interactive Charts with Jupyter Widgets Plotly, Altair, Bokeh, Pydeck, & More… | render_widget decorator
- Implementing Folium for Location-Based Heatmaps render.ui decorator
- Enhancing DataFrames with Filters and Selection Modes render.data_frame, render.DataGrid, render.DataTable, etc.
- Additional Rendering Options, Final Touches and Next Steps
- Part 5 Overview
- Modifying HTML and CSS in Shiny
- Adding a Logo Image
- Styling Labels and Containers Aligning our Image w/ the Title — Custom Divs
- Customizing Altair Charts Gridlines, Font, Axis Labels, Etc.
- Customizing Plotly Visualizations
- Customizing Seaborn & Folium Heatmaps
- Final Touches, Clean Up, Recap and Next Steps
- Final words! Like & Subscribe pretty please!!
Taught by
Keith Galli
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