Build Awesome Web Apps and Dashboards with Python - Full Shiny for Python Course

Build Awesome Web Apps and Dashboards with Python - Full Shiny for Python Course

Keith Galli via YouTube Direct link

- Further customization of our app adding title, using CSV data, dynamic input

8 of 47

8 of 47

- Further customization of our app adding title, using CSV data, dynamic input

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Classroom Contents

Build Awesome Web Apps and Dashboards with Python - Full Shiny for Python Course

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  1. 1 - About Shiny for Python & Course Overview
  2. 2 - Intro to Shiny & Gallery Examples
  3. 3 - Getting Started with the Shinylive Playground
  4. 4 - Building a custom visualization with Shinylive
  5. 5 - Easily sharing the code/application for a Shinylive app
  6. 6 - Building a Shiny Express App locally VSCode
  7. 7 - How to run app if you're not using VSCode
  8. 8 - Further customization of our app adding title, using CSV data, dynamic input
  9. 9 - Deploying our Shiny app to the web
  10. 10 - Part 2 Overview
  11. 11 - Getting Started with Code Part 2
  12. 12 - Adding Shiny Components Inputs, Outputs, & Display Messages
  13. 13 - Creating an Additional Visualization Sales Over Time by City
  14. 14 - What are Reactive.Calcs and How Do We Use Them Properly? DataFrame Best Practices
  15. 15 - Creating an Additional Visualization Sales Over Time by City — Continued
  16. 16 - Filtering City Data with Select Inputs UI.Input_Selectize
  17. 17 - Rendering Shiny Inputs Within Text
  18. 18 - Quick Formatting Adjustments
  19. 19 - Understanding the Shiny Reactivity Model How Does Shiny Render Things?
  20. 20 - Adding a Checkbox Input to Change Out Bar Chart Marker Colors
  21. 21 - Deploying Our Updated App!
  22. 22 - Advanced Concepts in Shiny Reactivity Reactive.Effect, Reactive.Event, Reactive.Isolate, Reactive.Invalidate_Later & Other Resources
  23. 23 - Thank you to Posit Connect, Our Sponsor
  24. 24 - Part 3 Overview
  25. 25 - Using Shiny Templates to Get Started Fast
  26. 26 - Using Layout Components to Customize our Apps Cards, Sidebars, Tabs, etc.
  27. 27 - Adding a Sidebar within a Card
  28. 28 - Adding a Card with Tabs to Display Various Visualizations
  29. 29 - Structuring Data in Columns / Grids layout_columns & layout_column_wrap
  30. 30 - Final Touches & Tips Filling in Visualizations into our Tab Views
  31. 31 - Part 4 Overview
  32. 32 - Getting Setup with the Code cloning branch from GitHub
  33. 33 - Adding Matplotlib-based visualizations render.plot Shiny for Python decorator
  34. 34 - Create a Seaborn Heatmap Chart Sales Volume by Hour of the Day
  35. 35 - Creating Interactive Charts with Jupyter Widgets Plotly, Altair, Bokeh, Pydeck, & More… | render_widget decorator
  36. 36 - Implementing Folium for Location-Based Heatmaps render.ui decorator
  37. 37 - Enhancing DataFrames with Filters and Selection Modes render.data_frame, render.DataGrid, render.DataTable, etc.
  38. 38 - Additional Rendering Options, Final Touches and Next Steps
  39. 39 - Part 5 Overview
  40. 40 - Modifying HTML and CSS in Shiny
  41. 41 - Adding a Logo Image
  42. 42 - Styling Labels and Containers Aligning our Image w/ the Title — Custom Divs
  43. 43 - Customizing Altair Charts Gridlines, Font, Axis Labels, Etc.
  44. 44 - Customizing Plotly Visualizations
  45. 45 - Customizing Seaborn & Folium Heatmaps
  46. 46 - Final Touches, Clean Up, Recap and Next Steps
  47. 47 - Final words! Like & Subscribe pretty please!!

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