Step-by-step training for 3D and advanced visualization in python and Matplotlib (with all the codes)
InstructorS. Emadedin HashemiComidoc has tracked 16 coupons for this course since 2025, last checked 26h ago. On average, a new coupon appears roughly every 21 days.
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The curriculum provides specific modules for various 3D structures, including bar charts, histograms, contour plots, wireframes, and surface plots.
Instruction extends to polar coordinate plotting for sine and tangent functions, as well as geospatial heatmap generation using Folium.
Editorial course preview
These 4 complementary views highlight concrete, legible examples from the course presentation.
This screenshot shows a Jupyter Notebook environment where Python code is used to create detailed 3D surface plots, demonstrating the syntax for rendering visualizations.
This notebook demonstrates how to customize 3D plots in Matplotlib by setting the colormap to viridis and removing edge colors for a smooth appearance.
This composite image showcases three distinct types of 3D visualizations, including a color-coded scatter plot, a smooth surface plot, and a geometric torus.
This composite image showcases four different types of 3D plots generated using Python libraries, including a bar chart, surface plots, and a spiral line graph.
A signal from before the displayed update indicates uncertainty regarding the practical utility of 3D plots in standard data workflows; note that the update label does not prove a correction to this concern.
The curriculum aligns with the goal of advanced visualization for researchers and analysts, though it assumes a baseline of Python knowledge.