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pipeline_wrapper.py
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pipeline_wrapper.py
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from sklearn.base import BaseEstimator, TransformerMixin
import ta
class TAFeaturesTransform(BaseEstimator, TransformerMixin):
"""Add all technical analysis features to dataframe.
Args:
df (pandas.core.frame.DataFrame): Dataframe base.
open (str): Name of 'open' column.
high (str): Name of 'high' column.
low (str): Name of 'low' column.
close (str): Name of 'close' column.
volume (str): Name of 'volume' column.
fillna(bool): if True, fill nan values.
Returns:
pandas.core.frame.DataFrame: Dataframe with new features.
"""
def __init__(self, open_column: str, high_column: str, low_column: str, close_column: str,
volume_column: str, fillna: bool = False, colprefix: str = ""):
self._open_column = open_column
self._high_column = high_column
self._low_column = low_column
self._close_column = close_column
self._volume_column = volume_column
self._fillna = fillna
self._colprefix = colprefix
def fit(self, X, y=None, **fit_params):
return self
def transform(self, X, **transform_params):
X = ta.add_all_ta_features(df=X, open=self._open_column, high=self._high_column,
low=self._low_column, close=self._close_column,
volume=self._volume_column, fillna=self._fillna,
colprefix=self._colprefix)
return X.values