tidyr
tidyr replaced separate() with a family that says what it does.
A side-by-side editorial comparison of dowhy and geopandas — release velocity, themes, recent moves, and the top alternatives to consider.
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.
GeoPandas bet everything on shapely 2 and Pyogrio, and is now paying down pandas 3
The library is in patch mode on the 1.1 line, split between pandas 3.0 compatibility work - Copy-on-Write, the new string dtype - and a run of bug fixes that includes two separate SQL-injection hardenings in to_postgis. The visible history reaches back to the 1.0 pre-releases, where GeoPandas dropped shapely<2 and PyGEOS entirely and switched its default I/O engine from Fiona to Pyogrio.
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.
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.
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.
The library is in patch mode on the 1.1 line, split between pandas 3.0 compatibility work - Copy-on-Write, the new string dtype - and a run of bug fixes that includes two separate SQL-injection hardenings in to_postgis. The visible history reaches back to the 1.0 pre-releases, where GeoPandas dropped shapely<2 and PyGEOS entirely and switched its default I/O engine from Fiona to Pyogrio.
The 1.0 cycle collapsed a pile of optional backends into one geometry engine and one I/O engine, and the releases since have been about surviving what moves underneath: pandas 3.0 changing copy semantics and string storage. Expect the compatibility burden, not new spatial capability, to set the release cadence for now.
Further 1.1.x patches tracking pandas 3.x behaviour changes are the most likely next move, with the repeated to_postgis fixes suggesting more scrutiny of SQL construction there. Nothing in these entries points to a 1.2 feature line.
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 geopandas.
tidyr replaced separate() with a family that says what it does.
modeltime built conformal intervals in, then went quiet on features.
performance keeps adding ways to check a model you have already fitted.
CmdStanPy is clearing deprecations ahead of a 2.0 it keeps announcing.
OpenHouse is hardening the seams where table policies and jobs quietly fail.
silx 3.0 moved its default Qt binding to PySide6 — a migration for everyone embedding it.
See all dowhy alternatives → · See all geopandas alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — python — within Analytics. dowhy and geopandas 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dowhy and geopandas 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.
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.
Top geopandas alternatives in Analytics are ranked by recent ship velocity. Browse the "geopandas alternatives" section above for the current picks, or visit /alternatives/geopandas for the full list with editorial commentary on each.