normality
Get Normality Statistics.
- Kurtosis: whether the kurtosis of a sample differs from the normal distribution.
- Skewness: whether the skewness of a sample differs from the normal distribution.
- Jarque-Bera: whether the sample data has the skewness and kurtosis matching a normal distribution.
- Shapiro-Wilk: whether a random sample comes from a normal distribution.
- Kolmogorov-Smirnov: whether two underlying one-dimensional probability distributions differ.
Example
from openbb import obb
stock_data = obb.equity.price.historical(symbol='TSLA', start_date='2023-01-01', provider='fmp').to_df()
obb.quantitative.normality(data=stock_data, target='close')
Parameters
- standard
| Name | Type | Description | Default | Optional |
|---|---|---|---|---|
| data | List[Data] | Time series data. | False | |
| target | str | Target column name. | False |
Returns
OBBject
results : NormalityModel
Normality tests summary. See qa_models.NormalityModel for details.