Lvr
lvr tells you which causes provoke which effects:
>>> from lvr import Lvr
>>> values = [789, 621, 109, 65, 45, 30, 27, 15, 12, 9]
>>> Lvr(values).summary(guess=True)
{'causes': 0.2, 'effects': 0.8, 'entropy_ratio': 0.71, 'pareto': True}
Links
code repository: https://hg.sr.ht/~bwe/lvr
docs: https://lvr.rtfd.io
Metadata
Release files for lvr 0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| lvr-0.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Release files / lvr-0.1.2-py3-none-any.whl
| Download URL | lvr-0.1.2-py3-none-any.whl |
|---|---|
| Size | 274.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
ce7d05ca814ca226a0a751f9807da69f6110154044275dbc30af4f79c80c368a
|
|
BLAKE2b-256 checksum How to use checksums |
cbc4173b0164c8696c605edfeca8d56ca1dce0ea8a0495377460f9d6a67a0f48
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.8.0 pkginfo/1.8.2 readme-renderer/33.0 requests/2.26.0 requests-toolbelt/0.9.1 urllib3/1.26.6 tqdm/4.63.0 importlib-metadata/4.11.2 keyring/23.5.0 rfc3986/2.0.0 colorama/0.4.4 CPython/3.9.9
|