| """Statistics Functions.""" |
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| from typing import Union |
|
|
| from numpy import ( |
| mean as mean_np, |
| ndarray, |
| std, |
| var as var_np, |
| ) |
| from pandas import DataFrame, Series |
| from scipy import stats |
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| def kurtosis_(data: Union[DataFrame, Series, ndarray]) -> float: |
| """Get Kurtosis. |
| |
| It is a measure of the "tailedness" of the probability distribution of a real-valued random variable. |
| """ |
| return stats.kurtosis(data) |
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| def skew_(data: Union[DataFrame, Series, ndarray]) -> float: |
| """Get Skewness. |
| |
| It is a measure of the asymmetry of the probability distribution of a |
| real-valued random variable about its mean. |
| """ |
| return stats.skew(data) |
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| def mean_(data: Union[DataFrame, Series, ndarray]) -> float: |
| """Get Mean which is the average of the numbers.""" |
| return mean_np(data) |
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| def std_dev_(data: Union[DataFrame, Series, ndarray]) -> float: |
| """Get Standard deviation that is a measure of the amount of variation or dispersion of a set of values.""" |
| return std(data) |
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| def var_(data: Union[DataFrame, Series, ndarray]) -> float: |
| """Get Variance that is a measure of the amount of variation or dispersion of a set of values.""" |
| return var_np(data) |
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|