Nightingale
I named this package Nightingale in honour of Florence Nightingale, The lady with the data.
Installation
You can use pip to install Nightingale:
pip install nightingale
Usage
Population Proportion
from nightingale import get_sample_size, PopulationProportion, get_z_score
print('z-score for 0.95 confidence:', get_z_score(confidence=0.95))
print('sample size:', get_sample_size(confidence=0.95, error_margin=0.05, population_size=1000))
print('with 10% group proportion:', get_sample_size(confidence=0.95, error_margin=0.05, population_size=1000, group_proportion=0.1))
population_proportion = PopulationProportion(sample_n=239, group_proportion=0.5)
print('error:', population_proportion.get_error(confidence=0.95))
Ordinary Least Squares (OLS)
import pandas as pd
import numpy as np
from nightingale import OrdinaryLeastSquares
data = pd.DataFrame({
'x': np.random.normal(size=20, scale=5),
'y': np.random.normal(size=20, scale=5),
})
data['z'] = data['x'].values + data['y'].values + np.random.normal(size=20, scale=1)
print('data:')
display(data.head())
ols = OrdinaryLeastSquares(data=data, formula='z ~ x + y')
print('ols results:')
display(ols.table)
print('r-squared:', ols.r_squared)
print('adjusted r-squared:', ols.adjusted_r_squared)
ANOVA
References
z-score: https://stackoverflow.com/questions/20864847/probability-to-z-score-and-vice-versa-in-python
1 maintainer
Metadata
1 maintainer
Release files for nightingale 1.3
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| File | Size | Uploaded | Provenance | |
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| nightingale-1.3.tar.gz | 3.8 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| nightingale-1.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 9.9 kB
Release files / nightingale-1.3.tar.gz
| Download URL | nightingale-1.3.tar.gz |
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| Size | 3.8 kB |
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|
Release files / nightingale-1.3-py3-none-any.whl
| Download URL | nightingale-1.3-py3-none-any.whl |
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| Size | 6.1 kB |
| Tags | Python 3 |
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