human
Solve the following python programming problem given the following code:
# %load "preprocessing_transforms.py"
from sklearn.base import TransformerMixin, BaseEstimator
import pandas as pd
import heapq
import numpy as np

class BaseTransformer(BaseEstimator, TransformerMixin):
    def fit(self, X, y=None, **fit_params):
        return self

    def transform(self, X, **transform_params):
        return self

class ColumnSelector(BaseTransformer):
    """Selects columns from Pandas Dataframe"""

    def __init__(self, columns, c_type=None):
        self.columns = columns
        self.c_type = c_type

    def transform(self, X, **transform_params):
        cs = X[self.columns]
        if self.c_type is None:
            return cs
        else:
            return cs.astype(self.c_type)

class OmniEncoder(BaseTransformer):
    """
    Encodes a categorical variable using no more than k columns. As many values as possible
    are one-hot encoded, the remaining are fit within a binary encoded set of columns.
    If necessary some are dropped (e.g if (#unique_values) > 2^k).

    In deciding which values to one-hot encode, those that appear more frequently are
    preferred.
    """
    def __init__(self, max_cols=20):
        self.column_infos = {}
        self.max_cols = max_cols
        if max_cols < 3 or max_cols > 100:
            raise ValueError("max_cols {} not within range(3, 100)".format(max_cols))

    def fit(self, X, y=None, **fit_params):
        self.column_infos = {col: self._column_info(X[col], self.max_cols) for col in X.columns}
        return self

    def transform(self, X, **transform_params):
        return pd.concat(
            [self._encode_column(X[col], self.max_cols, *self.column_infos[col]) for col in X.columns],
            axis=1
        )

    @staticmethod
    def _encode_column(col, max_cols, one_hot_vals, binary_encoded_vals):
        num_one_hot = len(one_hot_vals)
        num_bits = max_cols - num_one_hot if len(binary_encoded_vals) > 0 else 0

        # http://stackoverflow.com/a/29091970/231589
        zero_base = ord('0')
        def...
Given the above code, generate some markdown instructions for it.
assistant
#Here is the Python code you requested.

Building a preprocessing pipeline
Notice the new OmniEncoder transformer and read more about its development in my learning log.