Analysis tools for machine learning projects
1. Usage
$ pip install analysis-tools
2. Tutorial
examples/titanic/eda.ipynb를 참고
from analysis_tools import eda, metrics
data = pd.DataFrame(..)
target = 'survived'
num_features = ['age', 'sibsp', 'parch', 'fare']
cat_features = data.columns.drop(num_features)
data[num_features] = data[num_features].astype('float32')
data[cat_features] = data[cat_features].astype('string')
eda.plot_missing_value(data)
eda.plot_features(data)
eda.plot_features_target(data, target)
eda.plot_corr(data.corr())
metrics.get_feature_importance(data, target)
1 maintainer
Metadata
1 maintainer
Release files for analysis-tools 0.3.2
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| analysis_tools-0.3.2.tar.gz | 15.0 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| analysis_tools-0.3.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 33.9 kB
Release files / analysis_tools-0.3.2.tar.gz
| Download URL | analysis_tools-0.3.2.tar.gz |
|---|---|
| Size | 15.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
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poetry/1.5.1 CPython/3.10.6 Linux/5.15.90.1-microsoft-standard-WSL2
|
Release files / analysis_tools-0.3.2-py3-none-any.whl
| Download URL | analysis_tools-0.3.2-py3-none-any.whl |
|---|---|
| Size | 19.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
poetry/1.5.1 CPython/3.10.6 Linux/5.15.90.1-microsoft-standard-WSL2
|
Security for analysis-tools 0.3.2
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