Skip to main content

Very Basic package make some usefull log transformation for scikit-learn

Project description

image

License: GPL v3 Python Repo Size PEP8 Poetry Coverage CI statics

Scikit-transformers : Scikit-learn + transformers

About

Basic package to enable usefull transformers in scikit-learn pipelines.

First transformer implemented is a LogTransformer, which is a simple wrapper around the numpy log function.

Installation

Using regular pip and venv tools :

python3 -m venv .venv
source .venv/bin/activate
pip install scikit-transformers

Usage

For a very basic usage :

import pandas as pd

from sktransf import LogTransformer

df = pd.DataFrame(
    { "a": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 
      "b": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
    }
)

    logger = LogTransformer()
    logger.fit_transform(df)
    df_transf = logger.transform(df)

Documentation

For generic use case, please refer to this notebook.

A complete documentation will be soon available here.

Contributing

Pull requests are welcome.

For major changes, please open an issue first to discuss what you would like to change.

For more information, please refer to the contributing file.

License

GPLv3

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

scikit_transformers-0.1.0.tar.gz (15.7 kB view details)

Uploaded Source

Built Distribution

scikit_transformers-0.1.0-py3-none-any.whl (16.4 kB view details)

Uploaded Python 3

File details

Details for the file scikit_transformers-0.1.0.tar.gz.

File metadata

  • Download URL: scikit_transformers-0.1.0.tar.gz
  • Upload date:
  • Size: 15.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.7.0 CPython/3.11.3 Linux/6.5.0-14-generic

File hashes

Hashes for scikit_transformers-0.1.0.tar.gz
Algorithm Hash digest
SHA256 0192a7901bad353b447fd641b4f678887f74e885ce61b6069cb890dbee709b95
MD5 275e74e73459c1faeb28370fc16ca534
BLAKE2b-256 d306a25120c7cf9a0e72992ffbcad8c94ceb0f8c7f61b81e505c865e9fdf0f74

See more details on using hashes here.

File details

Details for the file scikit_transformers-0.1.0-py3-none-any.whl.

File metadata

File hashes

Hashes for scikit_transformers-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 0553c657b5275bb780fc4d8a5440976f725aba501d01342e5431082d18f9412b
MD5 a853e427ba249f0a78b1cac45eb30d9e
BLAKE2b-256 def441dd103d6a3578d9ccbb83449425c31eaf2e476e848c1ed66d0e44b2b4e7

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page