f_score

hhpy.ds.f_score(y_true: Union[pandas.core.series.Series, str], y_pred: Union[pandas.core.series.Series, str], df: pandas.core.frame.DataFrame = None, dropna: bool = True, f: Callable = <function r2_score>, groupby: Union[list, str] = None, f_name: str = None) → Union[pandas.core.frame.DataFrame, float]

generic scoring function base on pandas DataFrame.

Parameters:

• y_true – true values as name of df or vector data
• y_pred – predicted values as name of df or vector data
• df – pandas DataFrame containing true and predicted values [optional]
• dropna – whether to dropna values [optional]
• f – scoreing function to apply, default is sklearn.metrics.r2_score, should return a scalar value. [optional]
• groupby – if supplied then the result is returned for each group level [optional]
• f_name – name of the scoreing function, by default uses .__name__ property of function [optional]

Returns:

if groupby is supplied: pandas DataFrame, else: scalar value