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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


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

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