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33 - Adding Matplotlib-based visualizations (render.plot Shiny for Python decorator)
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34 - Create a Seaborn Heatmap Chart (Sales Volume by Hour of the Day)
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35 - Creating Interactive Charts with Jupyter Widgets (Plotly, Altair, Bokeh, Pydeck, & More…) | render_widget decorator
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36 - Implementing Folium for Location-Based Heatmaps (render.ui decorator)
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37 - Enhancing DataFrames with Filters and Selection Modes (render.data_frame, render.DataGrid, render.DataTable, etc.)
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38 - Additional Rendering Options, Final Touches and Next Steps
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41 - Adding a Logo Image
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43 - Customizing Altair Charts (Gridlines, Font, Axis Labels, Etc.)
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46 - Final Touches, Clean Up, Recap and Next Steps
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47 - Final words! Like & Subscribe pretty please!!
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11 - Getting Started with Code (Part 2)
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12 - Adding Shiny Components (Inputs, Outputs, & Display Messages)
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13 - Creating an Additional Visualization (Sales Over Time by City)
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14 - What are Reactive.Calcs and How Do We Use Them Properly? (DataFrame Best Practices)
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15 - Creating an Additional Visualization (Sales Over Time by City) — Continued
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16 - Filtering City Data with Select Inputs (UI.Input_Selectize)