tidyr
tidyr replaced separate() with a family that says what it does.
Comparison · Analytics
dowhy vs dplyr
A side-by-side editorial comparison of dowhy and dplyr — release velocity, themes, recent moves, and the top alternatives to consider.
dowhy vs dplyr: 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 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.
dowhy vs dplyr: 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.
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.
Alternatives to dowhy and dplyr
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 dplyr.
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.
Recent activity from dowhy and dplyr
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 4mo agodplyrFull compliance with the R C API
- 6mo agodplyrfilter_out(), when_any() and three recoding verbs land in 1.2.0 ⚡
- 9mo agodowhyv0.14: Python 3.13 support and a new doubly robust estimator
- 1y agodowhyv0.13: Generalized Adjustment Criterion for effect estimation and missing data support in GCM
- 1y agodowhyv0.12: Python 3.12 compatibility, [experimental] support for time-series data, and extensions to new scenarios
- 2y agodowhyv0.11.1: Bug fixes and improvements
- 2y agodowhyv0.11: New GCM features and improved compatibility of GCM with CausalModel API
- 2y agodplyrNamespaced join_by() helpers and refreshed bundled datasets
- 2y agodplyrDeprecation message and setequal() consistency fixes
- 2y agodowhyv0.10.1: Minor fixes to main 0.10 release
- 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 dowhy and dplyr?
They serve adjacent needs but don't currently overlap on shipped themes. dowhy and dplyr 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 dplyr?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dowhy and dplyr 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 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.