tidyr
tidyr replaced separate() with a family that says what it does.
Comparison · Analytics
dowhy vs ggplot2
A side-by-side editorial comparison of dowhy and ggplot2 — release velocity, themes, recent moves, and the top alternatives to consider.
dowhy vs ggplot2: at a glance
What is dowhy?
DoWhy adds one estimation method a year and keeps its identification edge.
DoWhy is at v0.14, which added a doubly robust estimator and Python 3.13 support. The releases before it followed the same shape: v0.13 brought the Generalized Adjustment Criterion for identification, v0.12 added time-series effect estimation and a rank-based anomaly scorer. Between the feature releases sit patch versions handling pandas and CUDA breakage.
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.
dowhy vs ggplot2: editorial side-by-side
dowhy
0.0ANALYTICS
DoWhy adds one estimation method a year and keeps its identification edge.
◆ Current state
DoWhy is at v0.14, which added a doubly robust estimator and Python 3.13 support. The releases before it followed the same shape: v0.13 brought the Generalized Adjustment Criterion for identification, v0.12 added time-series effect estimation and a rank-based anomaly scorer. Between the feature releases sit patch versions handling pandas and CUDA breakage.
◆ Where it's heading
Two threads run through the window. The identification side — DoWhy's differentiator against libraries that only estimate — keeps gaining criteria, from frontdoor with multiple variables through the Generalized Adjustment Criterion. The GCM side grows separately with missing-data handling, classifier selection logic and calibration work. The two halves are converging on a single API rather than staying separate entry points.
◆ Prediction
Given the pace of one estimator or criterion per release and the experimental flags still on missing-data support in GCM, the next release most likely promotes existing experimental features rather than opening a new estimation family.
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 dowhy 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 dowhy or ggplot2.
modeltime
modeltime built conformal intervals in, then went quiet on features.
performance
performance keeps adding ways to check a model you have already fitted.
cmdstanpy
CmdStanPy is clearing deprecations ahead of a 2.0 it keeps announcing.
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.
See all dowhy alternatives → · See all ggplot2 alternatives →
Recent activity from dowhy and ggplot2
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agoggplot2Boxplots gain a quantile.type argument for SAS parity
- 6mo agoggplot2Interoperability fix across rlang versions
- 9mo agodowhyv0.14: Python 3.13 support and a new doubly robust estimator
- 9mo agoggplot2Regression cleanup after the 4.0 rewrite
- 11mo agoggplot2ggplot2 4.0 replaces S3 internals with S7 ⚡
- 1y agodowhyv0.13: Generalized Adjustment Criterion for effect estimation and missing data support in GCM
- 1y agoggplot2Standardised class predicates to prepare packages for 4.0
- 1y agodowhyv0.12: Python 3.12 compatibility, [experimental] support for time-series data, and extensions to new scenarios
- 2y agoggplot2Patterns and gradients in geom_sf, resolution() reverted
- 2y agodowhyv0.11.1: Bug fixes and improvements
- 2y agodowhyv0.11: New GCM features and improved compatibility of GCM with CausalModel API
- 2y agodowhyv0.10.1: Minor fixes to main 0.10 release
Frequently asked questions
What is the difference between dowhy and ggplot2?
They serve adjacent needs but don't currently overlap on shipped themes. dowhy 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 dowhy better than ggplot2?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dowhy 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 dowhy?
Top dowhy alternatives in Analytics are ranked by recent ship velocity. Browse the "dowhy alternatives" section above for the current picks, or visit /alternatives/dowhy 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.