pasteur.extras.transformers.DatetimeTransformer#

class pasteur.extras.transformers.DatetimeTransformer(span='year.halfhour', **kwargs)[source]#

Attributes

deterministic

For a given output, the input is the same.

lossless

The decoded output equals the input.

name

stateful

Transformer fits variables.

Methods

fit(data[, ref])

Fits to the provided data

fit_transform(data[, ref])

rtype:

DataFrame

get_attributes()

rtype:

Mapping[str | tuple[str], Attribute]

get_factory(*args, **kwargs)

Returns a factory that registers this module to the system.

reduce(other)

reverse(data[, ref])

When reversing, the data column contains encoded data, whereas the ref column contains decoded/original data.

transform(data[, ref])

rtype:

DataFrame

deterministic = True#

For a given output, the input is the same.

fit(data, ref=None)[source]#

Fits to the provided data

fit_transform(data, ref=None)#
Return type:

DataFrame

get_attributes()[source]#
Return type:

Mapping[str | tuple[str], Attribute]

classmethod get_factory(*args, **kwargs)#

Returns a factory that registers this module to the system.

Any *args and **kwargs passed to this function will be saved and passed to the module’s __init__() method when calling build().

lossless = True#

The decoded output equals the input.

name: str = 'datetime'#
reduce(other)[source]#
reverse(data, ref=None)[source]#

When reversing, the data column contains encoded data, whereas the ref column contains decoded/original data. Therefore, the referred columns have to be decoded first.

Return type:

DataFrame | Series

stateful = True#

Transformer fits variables.

transform(data, ref=None)[source]#
Return type:

DataFrame