https://github.com/alchemine/analysis-tools
Analysis tools for machine learning projects
https://github.com/alchemine/analysis-tools
data-analysis explanatory-data-analysis machine-learning python
Last synced: 11 months ago
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Analysis tools for machine learning projects
- Host: GitHub
- URL: https://github.com/alchemine/analysis-tools
- Owner: alchemine
- Created: 2021-12-11T06:18:24.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2023-11-20T07:46:09.000Z (over 2 years ago)
- Last Synced: 2025-02-16T12:58:14.003Z (over 1 year ago)
- Topics: data-analysis, explanatory-data-analysis, machine-learning, python
- Language: Python
- Homepage: https://pypi.org/project/analysis-tools
- Size: 10.4 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Analysis tools for machine learning projects
## 1. Usage
```bash
$ pip install analysis-tools
```
## 2. Tutorial
[examples/titanic/eda.ipynb](https://github.com/alchemine/analysis-tools/blob/main/examples/titanic/eda.ipynb)를 참고
```python
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)
```
