🚀 CausalPy just hit 1,000+ ⭐ on GitHub — and crossed 120K downloads!
When A/B tests stop, CausalPy starts.
Bayesian. Interpretable. Open-source.
Huge thanks to everyone who’s contributed to the project.
👉Checkout CausalPy: dub.link/causalpy
#CausalPy #PyMCLabs #OpenSource #Bayesian #DataScience
When A/B tests stop, CausalPy starts.
Bayesian. Interpretable. Open-source.
Huge thanks to everyone who’s contributed to the project.
👉Checkout CausalPy: dub.link/causalpy
#CausalPy #PyMCLabs #OpenSource #Bayesian #DataScience
June 23, 2025 at 5:12 PM
🚀 CausalPy just hit 1,000+ ⭐ on GitHub — and crossed 120K downloads!
When A/B tests stop, CausalPy starts.
Bayesian. Interpretable. Open-source.
Huge thanks to everyone who’s contributed to the project.
👉Checkout CausalPy: dub.link/causalpy
#CausalPy #PyMCLabs #OpenSource #Bayesian #DataScience
When A/B tests stop, CausalPy starts.
Bayesian. Interpretable. Open-source.
Huge thanks to everyone who’s contributed to the project.
👉Checkout CausalPy: dub.link/causalpy
#CausalPy #PyMCLabs #OpenSource #Bayesian #DataScience
Looks like a nice package for Causal Inference in Python: causalpy.readthedocs.io
CausalPy - causal inference for quasi-experiments — CausalPy 0.4.0 documentation
causalpy.readthedocs.io
November 24, 2024 at 3:44 PM
Looks like a nice package for Causal Inference in Python: causalpy.readthedocs.io
Python Ireland just released their PyCon 2024 recordings! 📽️
My talk on Causal Inference with @pymc-labs.bsky.social CausalPy package is here. Can we trust individual IV designs. What's the role of CI in industry?
Recording: youtu.be/-C4p4b2cUp8?...
Deck: nathanielf.github.io/talks/pycon_...
My talk on Causal Inference with @pymc-labs.bsky.social CausalPy package is here. Can we trust individual IV designs. What's the role of CI in industry?
Recording: youtu.be/-C4p4b2cUp8?...
Deck: nathanielf.github.io/talks/pycon_...
May 2, 2025 at 5:58 AM
Python Ireland just released their PyCon 2024 recordings! 📽️
My talk on Causal Inference with @pymc-labs.bsky.social CausalPy package is here. Can we trust individual IV designs. What's the role of CI in industry?
Recording: youtu.be/-C4p4b2cUp8?...
Deck: nathanielf.github.io/talks/pycon_...
My talk on Causal Inference with @pymc-labs.bsky.social CausalPy package is here. Can we trust individual IV designs. What's the role of CI in industry?
Recording: youtu.be/-C4p4b2cUp8?...
Deck: nathanielf.github.io/talks/pycon_...
Very quick support for CausalPy @benvincent.bsky.social. Draft PR will follow in a bit
December 20, 2025 at 3:00 PM
Very quick support for CausalPy @benvincent.bsky.social. Draft PR will follow in a bit
🎄✨ 𝐌𝐞𝐫𝐫𝐲 𝐂𝐡𝐫𝐢𝐬𝐭𝐦𝐚𝐬 𝐚𝐧𝐝 𝐇𝐚𝐩𝐩𝐲 𝐇𝐨𝐥𝐢𝐝𝐚𝐲𝐬 𝐟𝐫𝐨𝐦 𝐏𝐲𝐌𝐂 𝐋𝐚𝐛𝐬!
🎁 This holiday season, we want to thank everyone in our community for your support and enthusiasm. We’re grateful to see so many of you using PyMC-Marketing and CausalPy
#MerryChristmas #HappyNewYear #PyMCMarketing #CausalPy #Gratitude
🎁 This holiday season, we want to thank everyone in our community for your support and enthusiasm. We’re grateful to see so many of you using PyMC-Marketing and CausalPy
#MerryChristmas #HappyNewYear #PyMCMarketing #CausalPy #Gratitude
December 24, 2024 at 4:23 PM
🎄✨ 𝐌𝐞𝐫𝐫𝐲 𝐂𝐡𝐫𝐢𝐬𝐭𝐦𝐚𝐬 𝐚𝐧𝐝 𝐇𝐚𝐩𝐩𝐲 𝐇𝐨𝐥𝐢𝐝𝐚𝐲𝐬 𝐟𝐫𝐨𝐦 𝐏𝐲𝐌𝐂 𝐋𝐚𝐛𝐬!
🎁 This holiday season, we want to thank everyone in our community for your support and enthusiasm. We’re grateful to see so many of you using PyMC-Marketing and CausalPy
#MerryChristmas #HappyNewYear #PyMCMarketing #CausalPy #Gratitude
🎁 This holiday season, we want to thank everyone in our community for your support and enthusiasm. We’re grateful to see so many of you using PyMC-Marketing and CausalPy
#MerryChristmas #HappyNewYear #PyMCMarketing #CausalPy #Gratitude
💥 CausalPy 0.5.0 is out! Now supports multiple treated units in synthetic control — a big boost for geo-lift analysis and more.
📖 Learn more: dub.link/causalpy-v0-...
#CausalPy #CausalInference #PyMC
📖 Learn more: dub.link/causalpy-v0-...
#CausalPy #CausalInference #PyMC
July 29, 2025 at 1:36 PM
💥 CausalPy 0.5.0 is out! Now supports multiple treated units in synthetic control — a big boost for geo-lift analysis and more.
📖 Learn more: dub.link/causalpy-v0-...
#CausalPy #CausalInference #PyMC
📖 Learn more: dub.link/causalpy-v0-...
#CausalPy #CausalInference #PyMC
Very Handy!
The latest version of CausalPy introduces a new piecewise interrupted time series (ITS) class.
CausalPy is a popular Python library for modeling quasi-experimental data.
The new version comes with a brand new...
1/
#CausalSky #EconSky #EpiSky #MLSky #StatSky
The latest version of CausalPy introduces a new piecewise interrupted time series (ITS) class.
CausalPy is a popular Python library for modeling quasi-experimental data.
The new version comes with a brand new...
1/
#CausalSky #EconSky #EpiSky #MLSky #StatSky
March 13, 2026 at 9:29 AM
Very Handy!
The latest version of CausalPy introduces a new piecewise interrupted time series (ITS) class.
CausalPy is a popular Python library for modeling quasi-experimental data.
The new version comes with a brand new...
1/
#CausalSky #EconSky #EpiSky #MLSky #StatSky
The latest version of CausalPy introduces a new piecewise interrupted time series (ITS) class.
CausalPy is a popular Python library for modeling quasi-experimental data.
The new version comes with a brand new...
1/
#CausalSky #EconSky #EpiSky #MLSky #StatSky
📽 Great fun presenting at Python Ireland PyCON 2024 this weekend! 📽
I spoke about the probing uncertainty in causal estimands using PyMC Labs's and @benvincent.bsky.social 's CausalPy package.
Slides can be found here: nathanielf.github.io/talks/pycon_...
I spoke about the probing uncertainty in causal estimands using PyMC Labs's and @benvincent.bsky.social 's CausalPy package.
Slides can be found here: nathanielf.github.io/talks/pycon_...
November 18, 2024 at 6:43 AM
📽 Great fun presenting at Python Ireland PyCON 2024 this weekend! 📽
I spoke about the probing uncertainty in causal estimands using PyMC Labs's and @benvincent.bsky.social 's CausalPy package.
Slides can be found here: nathanielf.github.io/talks/pycon_...
I spoke about the probing uncertainty in causal estimands using PyMC Labs's and @benvincent.bsky.social 's CausalPy package.
Slides can be found here: nathanielf.github.io/talks/pycon_...
#CausalPy 0.6.0 drops an enhanced reporting layer:
cleaner tables, consistent summaries, and faster access to “so what?” insights.
A big step toward business-ready Bayesian outputs.
🧩Available on Github: dub.link/yyubQTR
#CausalPy #BayesianModeling
cleaner tables, consistent summaries, and faster access to “so what?” insights.
A big step toward business-ready Bayesian outputs.
🧩Available on Github: dub.link/yyubQTR
#CausalPy #BayesianModeling
November 26, 2025 at 2:36 PM
#CausalPy 0.6.0 drops an enhanced reporting layer:
cleaner tables, consistent summaries, and faster access to “so what?” insights.
A big step toward business-ready Bayesian outputs.
🧩Available on Github: dub.link/yyubQTR
#CausalPy #BayesianModeling
cleaner tables, consistent summaries, and faster access to “so what?” insights.
A big step toward business-ready Bayesian outputs.
🧩Available on Github: dub.link/yyubQTR
#CausalPy #BayesianModeling
Want to build the future of decision intelligence?
Join #PyMC Labs in contributing to #CausalPy; open-source, Bayesian-powered causal inference for real-world problems.
🚀Watch onboarding: dub.link/3hk7lU0
🧩GitHub: github.com/pymc-labs/Ca...
#CausalInference #OpenSource
Join #PyMC Labs in contributing to #CausalPy; open-source, Bayesian-powered causal inference for real-world problems.
🚀Watch onboarding: dub.link/3hk7lU0
🧩GitHub: github.com/pymc-labs/Ca...
#CausalInference #OpenSource
Contributing to CausalPy: A Comprehensive Guide for Python Developers
Enjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube.
dub.link
January 27, 2026 at 1:36 PM
Want to build the future of decision intelligence?
Join #PyMC Labs in contributing to #CausalPy; open-source, Bayesian-powered causal inference for real-world problems.
🚀Watch onboarding: dub.link/3hk7lU0
🧩GitHub: github.com/pymc-labs/Ca...
#CausalInference #OpenSource
Join #PyMC Labs in contributing to #CausalPy; open-source, Bayesian-powered causal inference for real-world problems.
🚀Watch onboarding: dub.link/3hk7lU0
🧩GitHub: github.com/pymc-labs/Ca...
#CausalInference #OpenSource
Thanks 😄 Actually, @nathanielforde.bsky.social ported this implementation into causalpy causalpy.readthedocs.io/en/stable/no... Check it out :)
Instrumental Variable Modelling (IV) with pymc models — CausalPy 0.5.0 documentation
causalpy.readthedocs.io
October 22, 2025 at 3:10 PM
Thanks 😄 Actually, @nathanielforde.bsky.social ported this implementation into causalpy causalpy.readthedocs.io/en/stable/no... Check it out :)
In June we expanded on the instrumental variable documentation in CausalPy and made use of numpyro samplers to massively speed up sampling times for the IV class in CausalPy:
causalpy.readthedocs.io/en/latest/no...
causalpy.readthedocs.io/en/latest/no...
January 1, 2025 at 3:59 PM
In June we expanded on the instrumental variable documentation in CausalPy and made use of numpyro samplers to massively speed up sampling times for the IV class in CausalPy:
causalpy.readthedocs.io/en/latest/no...
causalpy.readthedocs.io/en/latest/no...
Agentic Causal Inference is here! 🙌
By connecting cursor to marimo via MCP, Gemini 3 Pro can execute and iterate on CausalPy models in real-time. From automated sensitivity analysis to Bayesian transparency!
👉Watch: ggl.link/Ifw0lVt
#CausalPy #AgenticAI
By connecting cursor to marimo via MCP, Gemini 3 Pro can execute and iterate on CausalPy models in real-time. From automated sensitivity analysis to Bayesian transparency!
👉Watch: ggl.link/Ifw0lVt
#CausalPy #AgenticAI
January 14, 2026 at 1:33 PM
Agentic Causal Inference is here! 🙌
By connecting cursor to marimo via MCP, Gemini 3 Pro can execute and iterate on CausalPy models in real-time. From automated sensitivity analysis to Bayesian transparency!
👉Watch: ggl.link/Ifw0lVt
#CausalPy #AgenticAI
By connecting cursor to marimo via MCP, Gemini 3 Pro can execute and iterate on CausalPy models in real-time. From automated sensitivity analysis to Bayesian transparency!
👉Watch: ggl.link/Ifw0lVt
#CausalPy #AgenticAI
Since @stephenjwild.bsky.social kindly added me to the Bayesian starterpack, figured i'd say Hi (+ thanks) to any new followers! Welcome!
I'm an Irish 🇮🇪 data scientist, and open source contributor to the PyMC, CausalPy eco-system.
Some recent work on Bayesian CFA + SEM:
bsky.app/profile/nath...
I'm an Irish 🇮🇪 data scientist, and open source contributor to the PyMC, CausalPy eco-system.
Some recent work on Bayesian CFA + SEM:
bsky.app/profile/nath...
📈 New Bayesian SEM and CFA models in PyMC 📉
A deep dive into psychometric models of survey data. We focus on the explore/exploit dynamics of modern Bayesian workflow, highlighting the flexibility of Bayesian approaches to Structural Equation Models.
nathanielf.github.io/posts/post-w...
A deep dive into psychometric models of survey data. We focus on the explore/exploit dynamics of modern Bayesian workflow, highlighting the flexibility of Bayesian approaches to Structural Equation Models.
nathanielf.github.io/posts/post-w...
September 1, 2024 at 7:07 PM
Since @stephenjwild.bsky.social kindly added me to the Bayesian starterpack, figured i'd say Hi (+ thanks) to any new followers! Welcome!
I'm an Irish 🇮🇪 data scientist, and open source contributor to the PyMC, CausalPy eco-system.
Some recent work on Bayesian CFA + SEM:
bsky.app/profile/nath...
I'm an Irish 🇮🇪 data scientist, and open source contributor to the PyMC, CausalPy eco-system.
Some recent work on Bayesian CFA + SEM:
bsky.app/profile/nath...
🎙️ In a recent discussion, @twiecki.bsky.social and Christian Luhmann reflected on their experiences building high-performing remote teams at PyMC Labs, sharing successes, challenges, and lessons learned. Here’s a glimpse:
🔗 youtu.be/AjPfgdS29OY
#Interview #PyMCMarketing #CausalPy
🔗 youtu.be/AjPfgdS29OY
#Interview #PyMCMarketing #CausalPy
December 16, 2024 at 3:24 PM
🎙️ In a recent discussion, @twiecki.bsky.social and Christian Luhmann reflected on their experiences building high-performing remote teams at PyMC Labs, sharing successes, challenges, and lessons learned. Here’s a glimpse:
🔗 youtu.be/AjPfgdS29OY
#Interview #PyMCMarketing #CausalPy
🔗 youtu.be/AjPfgdS29OY
#Interview #PyMCMarketing #CausalPy
Learn Bayesian regression modeling from the people building #PyMC, #Bambi & #CausalPy.
4 weeks. Live sessions. Real-world use cases.
👉 Registration now open: dub.link/2CDdYLK
#BayesianStatistics #Baysian
4 weeks. Live sessions. Real-world use cases.
👉 Registration now open: dub.link/2CDdYLK
#BayesianStatistics #Baysian
February 2, 2026 at 2:14 PM
Learn Bayesian regression modeling from the people building #PyMC, #Bambi & #CausalPy.
4 weeks. Live sessions. Real-world use cases.
👉 Registration now open: dub.link/2CDdYLK
#BayesianStatistics #Baysian
4 weeks. Live sessions. Real-world use cases.
👉 Registration now open: dub.link/2CDdYLK
#BayesianStatistics #Baysian
- Alexandre Andorra's new Claude Code skill for causal inference with PyMC, CausalPy, and DoWhy: DAGs and quasi-experiments included
- New causal jobs - industry and academia
4/
- New causal jobs - industry and academia
4/
April 19, 2026 at 9:11 AM
- Alexandre Andorra's new Claude Code skill for causal inference with PyMC, CausalPy, and DoWhy: DAGs and quasi-experiments included
- New causal jobs - industry and academia
4/
- New causal jobs - industry and academia
4/
✨ This year, we saw many new contributors contribute to PyMC-Marketing & CausalPy. Their work has made a real difference.
🌱 Some are first-time contributors, while others are experienced developers.
🙏 Thank you to everyone who contributed this year we’re excited to see what’s next!
🌱 Some are first-time contributors, while others are experienced developers.
🙏 Thank you to everyone who contributed this year we’re excited to see what’s next!
January 3, 2025 at 1:46 PM
✨ This year, we saw many new contributors contribute to PyMC-Marketing & CausalPy. Their work has made a real difference.
🌱 Some are first-time contributors, while others are experienced developers.
🙏 Thank you to everyone who contributed this year we’re excited to see what’s next!
🌱 Some are first-time contributors, while others are experienced developers.
🙏 Thank you to everyone who contributed this year we’re excited to see what’s next!
A new AI review! pymc-labs/CausalPy ⭐3.9/5.0
CausalPy is a research-oriented Python library for quasi-experimental causal inference, built around a “Bayesian-first” workflow using PyMC (with optional OLS baselines via scikit-learn/statsmodels-style modeling).
https://gitrated.com/pymc-labs/CausalPy
CausalPy is a research-oriented Python library for quasi-experimental causal inference, built around a “Bayesian-first” workflow using PyMC (with optional OLS baselines via scikit-learn/statsmodels-style modeling).
https://gitrated.com/pymc-labs/CausalPy
April 11, 2026 at 8:39 PM
A new AI review! pymc-labs/CausalPy ⭐3.9/5.0
CausalPy is a research-oriented Python library for quasi-experimental causal inference, built around a “Bayesian-first” workflow using PyMC (with optional OLS baselines via scikit-learn/statsmodels-style modeling).
https://gitrated.com/pymc-labs/CausalPy
CausalPy is a research-oriented Python library for quasi-experimental causal inference, built around a “Bayesian-first” workflow using PyMC (with optional OLS baselines via scikit-learn/statsmodels-style modeling).
https://gitrated.com/pymc-labs/CausalPy
It makes sense. Fwiw though, I think it's hard to have good intuition these details with out a concrete sense of the DGP. So much opportunity for illegal contrasts that throw off the estimator. Iirc there is an imputation based estimator for Staggered DiD in CausalPy...
July 7, 2026 at 8:58 PM
It makes sense. Fwiw though, I think it's hard to have good intuition these details with out a concrete sense of the DGP. So much opportunity for illegal contrasts that throw off the estimator. Iirc there is an imputation based estimator for Staggered DiD in CausalPy...
Final call! Our #Bayesian Marketing Analytics course starts Monday, Sept 7.
Learn live with the team behind #PyMC, PyMC-Marketing, & CausalPy:
- Interactive coding (MMM & CLV)
- Bring your own data
- Private Discord Q&A
Register: dub.sh/CAtxlsn
#MarketingAnalytics
Learn live with the team behind #PyMC, PyMC-Marketing, & CausalPy:
- Interactive coding (MMM & CLV)
- Bring your own data
- Private Discord Q&A
Register: dub.sh/CAtxlsn
#MarketingAnalytics
September 3, 2026 at 1:03 PM
Final call! Our #Bayesian Marketing Analytics course starts Monday, Sept 7.
Learn live with the team behind #PyMC, PyMC-Marketing, & CausalPy:
- Interactive coding (MMM & CLV)
- Bring your own data
- Private Discord Q&A
Register: dub.sh/CAtxlsn
#MarketingAnalytics
Learn live with the team behind #PyMC, PyMC-Marketing, & CausalPy:
- Interactive coding (MMM & CLV)
- Bring your own data
- Private Discord Q&A
Register: dub.sh/CAtxlsn
#MarketingAnalytics
Staggered Difference-in-Differences — CausalPy 0.8.1 documentation
causalpy.readthedocs.io
July 7, 2026 at 9:32 PM
Psysyncon is the only synth implementation in Python I know that comes with some sort of unit tests (though I haven’t reviewed them thoroughly). SCPI looks very promising, but no tests unfortunately. CausalPy has a Bayesian implementation. There’s also one called SyntheticControlMethods (no tests).
November 5, 2024 at 9:40 PM
Psysyncon is the only synth implementation in Python I know that comes with some sort of unit tests (though I haven’t reviewed them thoroughly). SCPI looks very promising, but no tests unfortunately. CausalPy has a Bayesian implementation. There’s also one called SyntheticControlMethods (no tests).
CausalPy, a Python package focussing on causal inference in quasi-experimental settings. The package allows for sophisticated Bayesian model fitting methods to be used in addition to traditional OLS. github.com/pymc-labs/Ca...
GitHub - pymc-labs/CausalPy: A Python package for causal inference in quasi-experimental settings
A Python package for causal inference in quasi-experimental settings - GitHub - pymc-labs/CausalPy: A Python package for causal inference in quasi-experimental settings
github.com
November 8, 2023 at 7:19 AM
CausalPy, a Python package focussing on causal inference in quasi-experimental settings. The package allows for sophisticated Bayesian model fitting methods to be used in addition to traditional OLS. github.com/pymc-labs/Ca...
- New Interrupted Time Series module in CausalPy + a tutorial
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Join us at: causalpython.io (it's free!)
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Join us at: causalpython.io (it's free!)
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Causal Python || Your go-to resource for learning about Causality in Python
A page where you can learn about causal inference in Python, causal discovery in Python and causal structure learning in Python. How to causal inference in Python?
causalpython.io
March 8, 2026 at 12:22 PM
- New Interrupted Time Series module in CausalPy + a tutorial
--------
We'll start sending today's issue at 9am PT / 12pm ET / 6pm CET (Sunday)
Join us at: causalpython.io (it's free!)
2/2
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We'll start sending today's issue at 9am PT / 12pm ET / 6pm CET (Sunday)
Join us at: causalpython.io (it's free!)
2/2