medoed
Библиотека для расчета минимального определяемого эффекта (MDE) в A/B тестах.
Установка
pip install medoed
Пример использования
from medoed import MDECalculator
mde_calculator = MDECalculator(
pre_experiment_data=pre_experiment_data,
date_field='install_date',
metrics=['revenue', 'retention'],
historical_data=historical_data,
strata=['geo', 'platform'],
alpha=0.05,
power=0.8,
outliers_handling_method='replace_threshold',
outliers_threshold_quantile=0.995,
outlier_type='upper',
test_days=30,
sample_size=10000,
are_correction=True,
continuous_alternative='two-sided'
)
df_mde = mde_calculator.calculate(n_processes=8)
df_mde
Требования
- Python 3.8+
- pandas 1.3+
- numpy 1.20+
- scipy 1.7+
- statsmodels 0.13+
- otvertka 0.1.10+
- tqdm 4.65+
Лицензия
MIT
1 maintainer
Metadata
1 maintainer
Release files for medoed 0.1.8
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| medoed-0.1.8.tar.gz | 270.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| medoed-0.1.8-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 279.1 kB
Release files / medoed-0.1.8.tar.gz
| Download URL | medoed-0.1.8.tar.gz |
|---|---|
| Size | 270.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/6.0.1 CPython/3.13.0
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Release files / medoed-0.1.8-py3-none-any.whl
| Download URL | medoed-0.1.8-py3-none-any.whl |
|---|---|
| Size | 8.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/6.0.1 CPython/3.13.0
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