Sanofi-Public/CImpact
Causal inference library for timeseries analysis
This tool helps analysts and data scientists measure the real-world impact of specific events or changes on a trend over time. You provide historical data (time series) and information about when an intervention occurred. The output clearly shows the estimated effect of that intervention, complete with confidence intervals to help you make informed decisions.
Available on PyPI.
Use this if you need to rigorously quantify how an event like a marketing campaign, new treatment, or policy change affected a key metric, like sales, patient outcomes, or economic indicators.
Not ideal if you're only interested in predicting future trends without needing to isolate the specific impact of an event.
Stars
38
Forks
2
Language
Python
License
—
Category
Last pushed
Nov 27, 2025
Commits (30d)
0
Dependencies
17
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