clarite.describe.skewness

clarite.describe.skewness(data: pandas.core.frame.DataFrame, dropna: bool = False)

Return the skewness of each continuous variable

Parameters:

data: pd.DataFrame

The DataFrame to be described

dropna: bool

If True, drop rows with NA values before calculating skew. Otherwise the NA values propagate.

Returns:

result: pd.DataFrame

DataFrame listing three values for each continuous variable and NA for others: skew, zscore, and pvalue The test null hypothesis is that the skewness of the samples population is the same as the corresponding

normal distribution. The pvalue is the two-sided pvalue for the hypothesis test

Examples

>>> import clarite
>>> clarite.describe.skewness(df)
     Variable      skew    zscore        pvalue
0       pdias       NaN       NaN           NaN
1   longindex       NaN       NaN           NaN
2     durflow  2.754286  8.183515  2.756827e-16
3      height  0.583514  2.735605  6.226567e-03
4     begflow -0.316648 -1.549449  1.212738e-01