class_docstr: Sklearn-compatible estimator, for column-wise imputing DataFrames by replacing all ``NaNs`` and ``infs``
  with with average/extreme values from the same columns. It is basically a wrapper around
  :func:`~tsfresh.utilities.dataframe_functions.impute`.
  
  Each occurring ``inf`` or ``NaN`` in the DataFrame is replaced by
  
  * ``-inf`` -> ``min``
  * ``+inf`` -> ``max``
  * ``NaN`` -> ``median``
  
  This estimator - as most of the sklearn estimators - works in a two step procedure. First, the ``.fit``
  function is called where for each column the min, max and median are computed.
  Secondly, the ``.transform`` function is called which replaces the occurances of ``NaNs`` and ``infs`` using
  the column-wise computed min, max and median values.
docstr: Create a new PerColumnImputer instance, optionally with dictionaries containing replacements for
  ``NaNs`` and ``infs``.
  
  :param col_to_NINF_repl: Dictionary mapping column names to ``-inf`` replacement values
  :type col_to_NINF_repl: dict
  :param col_to_PINF_repl: Dictionary mapping column names to ``+inf`` replacement values
  :type col_to_PINF_repl: dict
  :param col_to_NAN_repl: Dictionary mapping column names to ``NaN`` replacement values
  :type col_to_NAN_repl: dict
code: def __init__(
      self,
      col_to_NINF_repl_preset=None,
      col_to_PINF_repl_preset=None,
      col_to_NAN_repl_preset=None,
  ):
      """
      Create a new PerColumnImputer instance, optionally with dictionaries containing replacements for
      ``NaNs`` and ``infs``.
  
      :param col_to_NINF_repl: Dictionary mapping column names to ``-inf`` replacement values
      :type col_to_NINF_repl: dict
      :param col_to_PINF_repl: Dictionary mapping column names to ``+inf`` replacement values
      :type col_to_PINF_repl: dict
      :param col_to_NAN_repl: Dictionary mapping column names to ``NaN`` replacement values
      :type col_to_NAN_repl: dict
      """
      self._col_to_NINF_repl = None
      self._col_to_PINF_repl = None
      self._col_to_NAN_repl = None
      self.col_to_NINF_repl_preset = col_to_NINF_repl_preset
      self.col_to_PINF_repl_preset = col_to_PINF_repl_preset
      self.col_to_NAN_repl_preset = col_to_NAN_repl_preset
  
file_path: tsfresh/tsfresh/transformers/per_column_imputer.py
imports: import pandas
  from sklearn.base import BaseEstimator, TransformerMixin
  from sklearn.exceptions import NotFittedError
  from tsfresh.utilities.dataframe_functions import get_range_values_per_column, impute_dataframe_range
label_desc: Use image node_id 1 to create a new PerColumnImputer object from inherited base classes: BaseEstimator, TransformerMixin with example: obj = PerColumnImputer(col_to_NINF_repl_preset, col_to_PINF_repl_preset, col_to_NAN_repl_preset)