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bittermelon vs ggcorrplot

A side-by-side editorial comparison of bittermelon and ggcorrplot — release velocity, themes, recent moves, and the top alternatives to consider.

bittermelon vs ggcorrplot: at a glance

Featurebittermelonggcorrplot
SectorAnalyticsAnalytics
Velocity score0.02.5
Sparks · 30d00
Top themesr-package, bitmap-fonts, greyscale, typographycorrelation, r, ggplot2, visualization
Last editorial update1h ago5h ago
WebsiteVisit →Visit →

What is bittermelon?

bittermelon is growing from binary bitmaps toward greyscale and color glyphs

The package manipulates bitmap fonts and bitmaps in R, and the recent direction is widening what a glyph can be. v2.3.1 adds greyscale font support by reading the experimental yaff levels property into pixmap glyphs with alpha derived from the level fraction, and makes writing a multi-colored glyph an error rather than silently clamping it. Earlier releases built out the same surface: bm_extract(), an interactive pixel picker, data frame coercion, and format support for other packages' bitmap types.

Read the full bittermelon trajectory →

What is ggcorrplot?

ggcorrplot came back after four years and found its significance markers had been lying

ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.

Read the full ggcorrplot trajectory →

bittermelon vs ggcorrplot: editorial side-by-side

B
bittermelon
ANALYTICS
0.0

bittermelon is growing from binary bitmaps toward greyscale and color glyphs

◆ Current state

The package manipulates bitmap fonts and bitmaps in R, and the recent direction is widening what a glyph can be. v2.3.1 adds greyscale font support by reading the experimental yaff levels property into pixmap glyphs with alpha derived from the level fraction, and makes writing a multi-colored glyph an error rather than silently clamping it. Earlier releases built out the same surface: bm_extract(), an interactive pixel picker, data frame coercion, and format support for other packages' bitmap types.

◆ Where it's heading

Two things are converging. The representation is moving beyond one-bit glyphs — pixmaps, color, and now greyscale levels with transparency — while the API gets stricter about the boundary between them, refusing to quietly downcast a color glyph on write. Separately, the package has been shedding weight: the embedded monobit copy was removed once it outgrew CRAN size limits, pushing format breadth onto a user-installed dependency.

◆ Prediction

Expect further greyscale and color work now that levels parsing exists — most likely writing that format rather than only reading it, since the write path is where the current release chose to draw a hard error instead.

G
ggcorrplot
ANALYTICS
2.5

ggcorrplot came back after four years and found its significance markers had been lying

◆ Current state

ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.

◆ Where it's heading

Both releases chase the same target: parity with the older corrplot package inside a ggplot2 object. Significance stars appended to coefficient labels, circle scaling, decimal control, then boxed cells and glyphs sized by absolute correlation — these are corrplot's visual vocabulary reimplemented where they can be composed with other ggplot2 layers. The bug fixes point the other way, at foundations: p-values matched to cells by name rather than row position, clustering computed on the unrounded matrix, tl.col actually applied.

◆ Prediction

With the corrplot look largely reproduced and the correctness backlog cleared, the remaining gap is the mixed upper/lower display corrplot supports; that is the natural next argument if the current release pace holds.

Alternatives to bittermelon and ggcorrplot

Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either bittermelon or ggcorrplot.

See all bittermelon alternatives → · See all ggcorrplot alternatives →

Recent activity from bittermelon and ggcorrplot

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 21d agoggcorrplotggcorrplot 0.3.0 adds boxed cells and correlation-sized squares
  2. 1mo agoggcorrplotggcorrplot 0.2.0 fixes significance markers broken by hc.order
  3. 4mo agobittermelonGreyscale font reading arrives; color glyphs no longer clamp silently
  4. 6mo agobittermelonBitmap extraction and a supported-format predicate
  5. 1y agobittermelonData frame coercion and an interactive pixel picker
  6. 2y agobittermelonEmbedded monobit removed; broader format support now needs a manual install
  7. 2y agobittermelonCombining-character test fixed after a Unicode package change
  8. 3y agobittermelonHex fonts can be read selectively by code point
  9. 3y agoggcorrplotggcorrplot 0.1.4
  10. 6y agoggcorrplotggcorrplot 0.1.3
  11. 7y agoggcorrplotggcorrplot 0.1.2
  12. 10y agoggcorrplotggcorrplot's first release: correlograms in ggplot2

Frequently asked questions

What is the difference between bittermelon and ggcorrplot?

They serve adjacent needs but don't currently overlap on shipped themes. ggcorrplot is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is bittermelon better than ggcorrplot?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggcorrplot is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to bittermelon?

Top bittermelon alternatives in Analytics are ranked by recent ship velocity. Browse the "bittermelon alternatives" section above for the current picks, or visit /alternatives/bittermelon-r for the full list with editorial commentary on each.

What are the best alternatives to ggcorrplot?

Top ggcorrplot alternatives in Analytics are ranked by recent ship velocity. Browse the "ggcorrplot alternatives" section above for the current picks, or visit /alternatives/ggcorrplot for the full list with editorial commentary on each.