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 type skew zscore pvalue 0 pdias categorical NaN NaN NaN 1 longindex categorical NaN NaN NaN 2 durflow continuous 2.754286 8.183515 2.756827e-16 3 height continuous 0.583514 2.735605 6.226567e-03 4 begflow continuous -0.316648 -1.549449 1.212738e-01