Helpful Package For Custom Transformers To Use In Sklearn Pipelines
Installation
pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple 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
- DFSelector
- DFObjectSelector
- DFFeatureUnion
- DFImputer
- DFImputerMostFrequent
- DFOrdinalEncoder
- DFStandardScaler
Metadata
Release files for scikit-learn-pipeline-utils 0.0.2
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| scikit-learn-pipeline-utils-0.0.2.tar.gz | 2.5 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| scikit_learn_pipeline_utils-0.0.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 5.6 kB
Release files / scikit-learn-pipeline-utils-0.0.2.tar.gz
| Download URL | scikit-learn-pipeline-utils-0.0.2.tar.gz |
|---|---|
| Size | 2.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
Release files / scikit_learn_pipeline_utils-0.0.2-py3-none-any.whl
| Download URL | scikit_learn_pipeline_utils-0.0.2-py3-none-any.whl |
|---|---|
| Size | 3.1 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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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
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