toad.transform module

class toad.transform.Combiner

Bases: sklearn.base.TransformerMixin

Combiner for merge data

dtypes

get the dtypes which is combiner used

Returns:(str|dict)

export(format=False)

export combine rules for score card

Parameters:

• format (bool) – if True, bins will be replace with string label for values
• to_json (str|IOBase) – io to write json file

Returns:

dict

fit(X, y=None, **kwargs)

fit combiner

Parameters:

• X (DataFrame|array-like) – features to be combined
• y (str|array-like) – target data or name of target in X
• method (str) – the strategy to be used to merge X, same as .merge, default is chi
• n_bins (int) – counts of bins will be combined

Returns:

self

set_rules(map, reset=False)

set rules for combiner

Parameters:

• map (dict|array-like) – map of splits
• reset (bool) – if need to reset combiner

Returns:

self

transform(X, **kwargs)

transform X by combiner

Parameters:

• X (DataFrame|array-like) – features to be transformed
• labels (bool) – if need to use labels for resulting bins, False by default

Returns:

array-like

class toad.transform.WOETransformer

Bases: sklearn.base.TransformerMixin

WOE transformer

export()

fit(X, y, **kwargs)

fit WOE transformer

Parameters:

• X (DataFrame|array-like) –
• y (str|array-like) –
• select_dtypes (str|numpy.dtypes) – ‘object’, ‘number’ etc. only selected dtypes will be transform,

transform(X, **kwargs)

transform woe

Parameters:

• X (DataFrame|array-like) –
• default (str) – ‘min’(default), ‘max’ - the strategy to be used for unknown group

Returns:

array-like

toad.transform.support_exclude(fn)

toad.transform.support_save_to_json(fn)

toad.transform.support_select_dtypes(fn)