dowhy
DoWhy adds one estimation method a year and keeps its identification edge.
Comparison · Analytics
dplyr vs ggplot2
A side-by-side editorial comparison of dplyr and ggplot2 — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r
dplyr vs ggplot2: at a glance
What is dplyr?
After two quiet years dplyr widened its verb vocabulary in one release
dplyr sat on patch releases from late 2023 until 1.2.0 landed in February 2026, and that release did a lot at once: a filter_out() counterpart to filter(), elementwise when_any() and when_all(), and three new recoding verbs alongside case_when(). It also rewrote if_else(), case_when() and coalesce() in C via vctrs, and promoted .by and reframe() from experimental to stable. The follow-up 1.2.1 is a compliance patch.
What is ggplot2?
ggplot2 swapped its object system out from under a decade of downstream code
The 4.0.0 release replaced ggplot2's S3 internals with S7 and made every geom's defaults settable from the theme, both breaking changes. The three releases since have been hotfixes cleaning up the fallout - regressions in geom_area(), position_stack() and the scale and guide systems - plus rlang interoperability repairs. The one genuinely new feature in that window is a quantile.type argument on boxplots.
dplyr vs ggplot2: editorial side-by-side
dplyr
0.0ANALYTICS
After two quiet years dplyr widened its verb vocabulary in one release
◆ Current state
dplyr sat on patch releases from late 2023 until 1.2.0 landed in February 2026, and that release did a lot at once: a filter_out() counterpart to filter(), elementwise when_any() and when_all(), and three new recoding verbs alongside case_when(). It also rewrote if_else(), case_when() and coalesce() in C via vctrs, and promoted .by and reframe() from experimental to stable. The follow-up 1.2.1 is a compliance patch.
◆ Where it's heading
The package is expanding its verb set deliberately, through published Tidyup design proposals rather than ad-hoc additions, and each new verb targets a case where the old idiom was error-prone - most obviously NA handling in negated filters. Underneath, hot paths keep moving from R into C, so the API grows while the runtime cost falls.
◆ Prediction
Expect the remaining experimental surface to follow .by and reframe() toward stable, and further hot paths to be rewritten in C via vctrs. The two Tidyup proposals referenced here suggest more of the filter and recode families is still being designed.
ggplot2
0.0ANALYTICS
ggplot2 swapped its object system out from under a decade of downstream code
◆ Current state
The 4.0.0 release replaced ggplot2's S3 internals with S7 and made every geom's defaults settable from the theme, both breaking changes. The three releases since have been hotfixes cleaning up the fallout - regressions in geom_area(), position_stack() and the scale and guide systems - plus rlang interoperability repairs. The one genuinely new feature in that window is a quantile.type argument on boxplots.
◆ Where it's heading
This is the tail of a long-telegraphed migration: 3.5.2 existed largely to give downstream packages the is_*() predicates and accessor functions they would need before 4.0 landed. With theme(geom) and from_theme(), styling is consolidating into the theme rather than being repeated per layer, which is the direction the extension ecosystem now has to follow.
◆ Prediction
Expect further 4.0.x patches as S7-related regressions surface in extension packages, and more of the per-geom default surface to migrate into element_geom(). The entries give no indication of a 4.1 feature line yet.
Alternatives to dplyr and ggplot2
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 dplyr or ggplot2.
OpenHouse
OpenHouse is hardening the seams where table policies and jobs quietly fail.
silx
silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.
statsmodels
statsmodels ships only what the ecosystem breaks — six releases, no new statistics.
StatsBase.jl
StatsBase.jl is in caretaker mode — correctness fixes in, dependency bumps out.
iris
Iris ships steadily on a two-a-year cadence, but its feed publishes only pointers.
See all dplyr alternatives → · See all ggplot2 alternatives →
Recent activity from dplyr and ggplot2
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agoggplot2Boxplots gain a quantile.type argument for SAS parity
- 4mo agodplyrFull compliance with the R C API
- 6mo agodplyrfilter_out(), when_any() and three recoding verbs land in 1.2.0 ⚡
- 6mo agoggplot2Interoperability fix across rlang versions
- 9mo agoggplot2Regression cleanup after the 4.0 rewrite
- 11mo agoggplot2ggplot2 4.0 replaces S3 internals with S7 ⚡
- 1y agoggplot2Standardised class predicates to prepare packages for 4.0
- 2y agoggplot2Patterns and gradients in geom_sf, resolution() reverted
- 2y agodplyrNamespaced join_by() helpers and refreshed bundled datasets
- 2y agodplyrDeprecation message and setequal() consistency fixes
- 3y agodplyrAll-NA join key fix and count() documentation
- 3y agodplyrJoins gain a relationship argument and warn far less often
Frequently asked questions
What is the difference between dplyr and ggplot2?
Both compete on the same themes — r — within Analytics. dplyr and ggplot2 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 dplyr better than ggplot2?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dplyr and ggplot2 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 dplyr?
Top dplyr alternatives in Analytics are ranked by recent ship velocity. Browse the "dplyr alternatives" section above for the current picks, or visit /alternatives/dplyr for the full list with editorial commentary on each.
What are the best alternatives to ggplot2?
Top ggplot2 alternatives in Analytics are ranked by recent ship velocity. Browse the "ggplot2 alternatives" section above for the current picks, or visit /alternatives/ggplot2 for the full list with editorial commentary on each.