Add Box Plot and Heatmap rows to the comparison - #31
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Box plot shows hwy by class from mpg; heatmap shows diamonds counts by cut and clarity. seaborn.objects is skipped for both: 0.13 has no boxplot mark and no rect mark, and pandas has no heatmap.
ggplot2's geom_bin2d bins discrete positions with a continuous binwidth, so the R heatmap came out as tiny disconnected tiles. Counting first and drawing geom_tile is the idiomatic recipe and matches the pivot-then-draw approach the matplotlib, seaborn, and hvPlot columns already take. Also stop seaborn from rotating the clarity labels.
tdhopper
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August 5, 2026 11:49
tdhopper
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Aug 5, 2026
Land the Box Plot and Heatmap rows stranded by the stacked merge of #31
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TL;DR
Two new plot rows — Box Plot (
hwybyclass, 9 of 10 columns) and Heatmap (diamondscut×claritycounts, 8 of 10) — bringing the site to 15 rows and 136 example cells. Gaps are API-honest: seaborn.objects has no boxplot or rect mark (verified against 0.13.2's mark list), and pandas.plothas no heatmap.Stacked on #30 (
content-refresh).Files to review (4):
Examples.ipynb(start here)render.pynamesdict (order controls page placement).tests/test_plots.pyINTRO.mdReviewer notes
geom_bin2d()is a trap on two discrete axes: it bins the integer factor positions with a continuous binwidth, yielding tiny disconnected tiles, and forcingbinwidth=c(1,1)misaligns tiles against tick labels by half a cell. The ggplot2/plotnine/lets-plot heatmaps use the R4DS idiom instead — count, thengeom_tile— which also mirrors the pivot-then-draw shape of the matplotlib/seaborn/hvPlot columns. Altair and plotly keep their built-in count aggregation, idiomatic there.Verified: notebook executes clean, 136/136 cells emit PNGs with zero error outputs, render + pytest pass, spot-checked ten of the new images.