PyPI Stats
burning-cost

insurance-causal

Causal inference for insurance pricing: double machine learning, price elasticity, heterogeneous treatment effects, and post-hoc rate change evaluation for UK personal lines.
PyPI GitHub
Downloads
Day
43
Week
123
Month
1.5K
Stars
0
Forks
0
Issues
0
Version
0.6.3

Package Insights

What's this?
Score breakdown - each component scores 0–100, weighted by percentage
Maintenance
70
Popularity
0
Adoption
31
Community
0
How the maintenance status was determined
Last commit
31 days ago
Monthly downloads
1,498
Active
Activity within 30 days
• Stable
Activity within 31-180 days
Minimal
Activity within 181-365 days, or no activity data
At Risk
No activity for > 365 days, but > 10,000 monthly downloads
Archived
Repository flagged as archived on GitHub
How the popularity category was determined
Monthly downloads
1,498
Stars
0
Stars per 1k downloads
0.00
Industry Standard
> 10,000,000 monthly downloads
Hidden Gem
< 0.5 stars per 1k downloads and > 100,000 monthly downloads
Community Favorite
> 5 stars per 1k downloads
Rising Star
Balanced ratio of stars to downloads
• Unknown
Fewer than 1,000 monthly downloads, or no star data
No star data — can't compute stars-to-downloads ratio.
How download momentum is calculated
Week daily avg
18
Month daily avg
50
Momentum
—
((week_daily_avg - month_daily_avg) / month_daily_avg) * 100
Momentum not reported for packages with < 5,000 monthly downloads — percentages are noisy at low volume.
Python version support tiers
requires_python
>=3.10
Cutting Edge
Minimum supported version is 3.12 or newer
• Modern
Minimum supported version is 3.9, 3.10, or 3.11
Legacy
Supports 3.8 or older (or Python 2)
Unknown
No requires_python specified or unparseable
License categories
License
MIT
• Permissive
MIT, Apache, BSD, ISC, Unlicense, CC0, etc.
Copyleft
GPL, LGPL, AGPL, MPL, EPL, etc.
Proprietary
Commercial, all rights reserved, custom EULAs
Unknown
No license specified, or none of the above match
How the release cadence was determined
Last release
32 days ago
Total releases
18
Releases/year
113.3
• Rapid
Last release within 365 days and > 12 releases/year
Regular
Last release within 365 days
Slow
Last release 366-730 days ago
Stalled
Last release > 730 days ago, or no releases
Unknown
No usable release date available
How contributor risk was determined
Contributors
3
Monthly downloads
1,498
High Load
≤ 2 contributors and ≥ 50,000 monthly downloads
Moderate Load
< 10 contributors and ≥ 500,000 monthly downloads
Low Load
< 25 contributors and ≥ 5,000,000 monthly downloads, or sole maintainer with ≥ 10,000 monthly downloads
• Balanced
Enough contributors for the package's popularity
Unknown
No contributor data available
Engagement
19
 
Issue Burden
-
per 1k stars
Discussions
-
per 1k stars
Fork Ratio
-
contrib / forks
Stale Release
No
 
PR Velocity
Quiet
 

Weekly Downloads

GitHub Stars

Not all downloads include detailed metadata. Breakdowns reflect the subset that does.

Downloads by OS

No OS data available

Python Versions

No Python version data available

Top Countries

1. KR KR
3
2. CA CA
1

Dependencies

10
19 optional dependencies

Used By

2

Package Information

License
MIT
First Release
March 9, 2026
Last Release
1 month ago
Last Commit
1 month ago
Latest Version
0.6.3
Total Releases
18
Contributors
3
Open PRs
0
Archived
No
Python Versions
3 3.10 3.11 3.12
Wheels
py3
Keywords
GIPP PS21/5 UK actuarial autoc blp catboost causal forest causal inference causal-inference consumer duty difference in differences dml dose response double machine learning double-machine-learning econometrics gates heterogeneous treatment effects hte insurance interrupted time series personal lines polars price elasticity pricing rate change renewal pricing riesz representer treatment effect uplift modelling
Topics
actuarial causal-inference double-machine-learning insurance python insurance-pricing catboost debiasing dml econometrics uk-insurance machine-learning pricing price-elasticity data-science
Tracking Since
March 15, 2026
Data Updated
May 3, 2026
Data Freshness
Fresh

Links