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"""
Contains routines for preprocessing data frames.
"""
from .preprocessor import _Preprocessor
[docs]class Substring(_Preprocessor):
"""
Substring extracts substrings from categorical columns
and unused string columns.
The preprocessor automatically iterates through
all categorical columns and unused string columns
in any data frame. The substring operator is then
applied to any such column for which the
unit matches `unit`.
.. code-block:: python
substr13 = getml.preprocessors.Substring(0, 3, "UCC")
pipe = getml.pipeline.Pipeline(
population=population_placeholder,
peripheral=[order_placeholder, trans_placeholder],
preprocessors=[substr13],
feature_learners=[feature_learner_1, feature_learner_2],
feature_selectors=feature_selector,
predictors=predictor,
share_selected_features=0.5
)
Args:
begin (int): Index of the beginning of the substring (starting from 0).
length (int): The length of the substring.
unit (str): The unit of all columns to which the proprocessor
should be applied.
"""
def __init__(self, begin, length, unit):
if not isinstance(begin, int):
raise TypeError("'begin' must be an integer!")
if not isinstance(length, int):
raise TypeError("'length' must be an integer!")
if not isinstance(unit, str):
raise TypeError("'unit' must be a string!")
if begin < 0:
raise ValueError("'begin' must be >= 0!")
if length <= 0:
raise ValueError("'length' must be > 0!")
if not unit:
raise ValueError("'unit' cannot be empty!")
super().__init__()
self.type = "Substring"
self.begin = begin
self.length = length
self.unit = unit