Python

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31 - Part 4 Overview

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32 - Getting Setup with the Code (cloning branch from GitHub)

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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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39 - Part 5 Overview

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40 - Modifying HTML and CSS in Shiny

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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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44 - Customizing Plotly Visualizations

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45 - Customizing Seaborn & Folium Heatmaps

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46 - Final Touches, Clean Up, Recap and Next Steps

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