← Back to home
Comparison · Analytics

ggmagnify vs quantities

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

Shared themes:r-package

ggmagnify vs quantities: at a glance

Featureggmagnifyquantities
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2, data-visualization, inset-plots, r-packageunits, measurement-uncertainty, error-propagation, r-package
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is ggmagnify?

A single-purpose ggplot2 inset tool, refining the same three arguments.

ggmagnify draws magnified insets of a region of a ggplot, with projection lines connecting the inset to its source area. The visible releases are all small refinements to how that inset looks — corner radius, fill between projection lines — plus one fix for inset themes being overridden. There are only three entries, so the picture is necessarily partial.

Read the full ggmagnify trajectory →

What is quantities?

The glue package that makes R carry units and uncertainty through the same calculation.

quantities combines the units and errors packages into one class so values keep both their measurement units and their uncertainty through arithmetic, subsetting and data frame operations. Recent releases have been narrow: fixes to the covariance and correlation implementations, and performance work on the data.frame methods. Most of the release traffic is coordination with its two parent packages.

Read the full quantities trajectory →

ggmagnify vs quantities: editorial side-by-side

G
ggmagnify
ANALYTICS
0.0

A single-purpose ggplot2 inset tool, refining the same three arguments.

◆ Current state

ggmagnify draws magnified insets of a region of a ggplot, with projection lines connecting the inset to its source area. The visible releases are all small refinements to how that inset looks — corner radius, fill between projection lines — plus one fix for inset themes being overridden. There are only three entries, so the picture is necessarily partial.

◆ Where it's heading

Work concentrates on the visual finish of the inset rather than on new capability, which is what a package with one job should look like. Two feature releases a week apart in early 2024 suggest a short burst of attention rather than sustained development, and the feed goes quiet after mid-2024.

◆ Prediction

Too few entries to call a direction with confidence; continued small styling arguments would be consistent with what is visible.

Q
quantities
ANALYTICS
0.0

The glue package that makes R carry units and uncertainty through the same calculation.

◆ Current state

quantities combines the units and errors packages into one class so values keep both their measurement units and their uncertainty through arithmetic, subsetting and data frame operations. Recent releases have been narrow: fixes to the covariance and correlation implementations, and performance work on the data.frame methods. Most of the release traffic is coordination with its two parent packages.

◆ Where it's heading

The design settled with 0.2.0, which made uncertainty unit-aware and added correlation and covariance support for quantities objects. Since then the package behaves like the integration layer it is — releasing when units, errors, dplyr or ggplot2 shift underneath it rather than on its own schedule. Several releases consist only of test repairs against upstream changes.

◆ Prediction

Expect the next release to follow a units or errors change rather than introduce new behaviour of its own.

Alternatives to ggmagnify and quantities

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 ggmagnify or quantities.

See all ggmagnify alternatives → · See all quantities alternatives →

Recent activity from ggmagnify and quantities

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

  1. 1y agoquantitiesFixes covariance and correlation implementations
  2. 2y agoquantitiesFaster data.frame methods
  3. 2y agoggmagnifyFixes inset theme override on supplied plots
  4. 2y agoggmagnifyAdds fill between projection lines
  5. 2y agoggmagnifyAdds corner radius for target and inset
  6. 3y agoquantitiesTest fixes for an upstream units change
  7. 3y agoquantitiesUncertainty becomes unit-aware; adds correlation support
  8. 5y agoquantitiesCompatibility fix for units 0.7-0
  9. 6y agoquantitiesFixes uncertainty propagation for offset unit conversions

Frequently asked questions

What is the difference between ggmagnify and quantities?

Both compete on the same themes — r-package — within Analytics. ggmagnify and quantities are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is ggmagnify better than quantities?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggmagnify and quantities are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to ggmagnify?

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

What are the best alternatives to quantities?

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