Skip to main content

Custom Pipeline Transformers for Sklearn Pipelines

Project description

Helpful Package For Custom Transformers To Use In Sklearn Pipelines

Installation

pip install scikit-learn-pipeline-utils

Quick Start

from sklearn_pipeline_utils import DFSelector
from sklearn.pipeline import Pipeline
import pandas as pd

df = pd.DataFrame({
    "col1": ["a", "b", "a"],
    "col2": [1, 2, 3]
})

pipeline = Pipeline([
    ("dfselectcol1", DFSelector("col1"))
    ])

print(pipeline.transform(df))
'''
expected result:
  col1
0    a
1    b
2    a
'''

Dataframe Transformers List

  1. DFSelector
  2. DFObjectSelector
  3. DFFeatureUnion
  4. DFImputer
  5. DFImputerMostFrequent
  6. DFOrdinalEncoder
  7. DFStandardScaler

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-learn-pipeline-utils-0.0.7.tar.gz (3.2 kB view details)

Uploaded Source

Built Distribution

File details

Details for the file scikit-learn-pipeline-utils-0.0.7.tar.gz.

File metadata

  • Download URL: scikit-learn-pipeline-utils-0.0.7.tar.gz
  • Upload date:
  • Size: 3.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.0

File hashes

Hashes for scikit-learn-pipeline-utils-0.0.7.tar.gz
Algorithm Hash digest
SHA256 fa9e84e0543bb975ed4be9e104d809fa48ad43163ca11013c70554cf0b790d0b
MD5 fc3c0b42bd72866f4364958c274bb6fa
BLAKE2b-256 89927a6b1f978ac573c540f31202aa52a5190a1ee3060edb50e628ea656947df

See more details on using hashes here.

File details

Details for the file scikit_learn_pipeline_utils-0.0.7-py3-none-any.whl.

File metadata

  • Download URL: scikit_learn_pipeline_utils-0.0.7-py3-none-any.whl
  • Upload date:
  • Size: 4.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/41.0.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/3.7.0

File hashes

Hashes for scikit_learn_pipeline_utils-0.0.7-py3-none-any.whl
Algorithm Hash digest
SHA256 3ebe9aab939fb165750473fabad639ab09f8cefdec9f5c33f7954a8622f21dcc
MD5 be812aad6e08d0ef1c970b18a2fb00d9
BLAKE2b-256 91970cf03a13cf98e6d69506fbdc24541608eeac3174c3b21db6010d54e36c9f

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