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Comparison · Analytics
Plotly vs statsmodels
A side-by-side editorial comparison of Plotly and statsmodels — release velocity, themes, recent moves, and the top alternatives to consider.
Plotly vs statsmodels: at a glance
What is Plotly?
Plotly is turning its cloud into a metered compute platform with an enterprise on-ramp.
Plotly ships on two tracks. Plotly Studio, the desktop AI app-builder, releases every one to two weeks and has spent v0.0.80 through v0.0.86 on credential handling, reasoning transparency, personalization and now the reliability of the agent session engine itself. Plotly Cloud is the louder track: since late May it has added viewer-seat pricing, domain verification, per-app compute modes with credit-metered billing, and customer-owned domains with managed TLS.
What is statsmodels?
statsmodels ships only what the ecosystem breaks — six releases, no new statistics.
Every release in this window is a compatibility release. 0.14.2 and 0.14.3 absorbed NumPy 2, 0.14.5 fixed an import failure caused by SciPy 1.16, and 0.14.6 did the same for pandas 3.0. The only additive change across two years is Pyodide support in 0.14.4, described in its own notes as one feature and no fixes. A 0.15.0.dev0 tag exists from 2023 and has not been followed by a 0.15 release.
Plotly vs statsmodels: editorial side-by-side
Plotly
6.3ANALYTICS
Plotly is turning its cloud into a metered compute platform with an enterprise on-ramp.
◆ Current state
Plotly ships on two tracks. Plotly Studio, the desktop AI app-builder, releases every one to two weeks and has spent v0.0.80 through v0.0.86 on credential handling, reasoning transparency, personalization and now the reliability of the agent session engine itself. Plotly Cloud is the louder track: since late May it has added viewer-seat pricing, domain verification, per-app compute modes with credit-metered billing, and customer-owned domains with managed TLS.
◆ Where it's heading
The Cloud releases are assembling the standard pieces of a hosting business in order — identity first (domain verification, explicitly framed as the step before SSO), then billing (viewer seats, then metered compute credits), and now production-grade serving (custom domains, automatic certificate renewal). Studio is being hardened as the authoring front end that feeds it: Universal Deployment pushed beyond Dash apps, credentials saved once and reused, a Winget channel to widen Windows installs, and in v0.0.86 a rebuilt session engine plus automatic retries so agent runs survive expired tokens. The two tracks converge on one funnel — author in Studio, deploy to Cloud, pay by compute consumed.
◆ Prediction
The Domain Verification entry names SSO as the next step and places it in the Enterprise tier, so single sign-on is the most likely Cloud release next. Studio should hold its one-to-two-week cadence, with the newly added app thumbnails pointing toward more work on browsing and organizing generated apps.
statsmodels
0.0ANALYTICS
statsmodels ships only what the ecosystem breaks — six releases, no new statistics.
◆ Current state
Every release in this window is a compatibility release. 0.14.2 and 0.14.3 absorbed NumPy 2, 0.14.5 fixed an import failure caused by SciPy 1.16, and 0.14.6 did the same for pandas 3.0. The only additive change across two years is Pyodide support in 0.14.4, described in its own notes as one feature and no fixes. A 0.15.0.dev0 tag exists from 2023 and has not been followed by a 0.15 release.
◆ Where it's heading
The library is being kept alive rather than developed: each release answers a break introduced upstream, and the interval between them is set by the NumPy, SciPy and pandas release calendars rather than by anything statsmodels is building. Two consecutive releases whose stated purpose was restoring the ability to import the package is the sharpest available signal about maintainer bandwidth. The 0.15 line remains a dev tag with no visible progress toward a release.
◆ Prediction
The next release is most likely another compatibility patch triggered by a NumPy, SciPy or pandas major, and nothing in these entries indicates 0.15 is close.
Alternatives to Plotly and statsmodels
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 Plotly or statsmodels.
Omni
Omni ships weekly, and almost every week the headline item is an AI feature.
silx
silx settles into maintenance a release after its PySide6 migration
aniread
aniread stops asking you to know which tracker wrote the file
Rho
Rho's release machinery finally produced a stable build — and it shipped no new product.
Usermaven
Usermaven closed the loop: data comes in from anywhere, and now it goes back out.
See all Plotly alternatives → · See all statsmodels alternatives →
Recent activity from Plotly and statsmodels
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 15d agoPlotlyCustom Domains in Plotly Cloud ⚡
- 25d agoPlotlyPlotly Studio v0.0.85: Breadcrumbs & minor bug fixes
- 1mo agoPlotlyPlotly Studio v0.0.84: Faster AI, Saved Credentials, and Winget Support
- 1mo agoPlotlyCompute Modes and App Sizing in Plotly Cloud ⚡
- 1mo agoPlotlyPlotly Studio 0.0.83: Dash Update and macOS Fixes
- 2mo agoPlotlyPlotly Studio v0.0.82: Override for credential redaction, stability fixes
- 8mo agostatsmodels0.14.6: restores importing under pandas 3.0
- 1y agostatsmodels0.14.5: restores importing under SciPy 1.16
- 1y agostatsmodels0.14.4: Pyodide support
- 1y agostatsmodels0.14.3: NumPy 2 environments and corrected macOS builds
- 2y agostatsmodels0.14.2: full NumPy 2 compatibility
- 2y agostatsmodelsstatsmodels 0.14.1 is a bug-fix release with no API changes
Frequently asked questions
What is the difference between Plotly and statsmodels?
They serve adjacent needs but don't currently overlap on shipped themes. Plotly is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is Plotly better than statsmodels?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Plotly is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to Plotly?
Top Plotly alternatives in Analytics are ranked by recent ship velocity. Browse the "Plotly alternatives" section above for the current picks, or visit /alternatives/plotly for the full list with editorial commentary on each.
What are the best alternatives to statsmodels?
Top statsmodels alternatives in Analytics are ranked by recent ship velocity. Browse the "statsmodels alternatives" section above for the current picks, or visit /alternatives/statsmodels for the full list with editorial commentary on each.