code: def _create_bars_data_for_mixed_kde_plot(
      counts: np.ndarray, max_kde_value: float
  ):
      """When showing a mixed KDE and bar plot, we want the bars to be on the same scale of y-values as the KDE values, \
      so we normalize the counts to sum to 4 times the max KDE value."""
      normalize_factor = 4 * max_kde_value / np.sum(counts)
      return counts * normalize_factor
  
file_path: deepchecks/deepchecks/utils/distribution/plot.py
imports: from functools import cmp_to_key
  from numbers import Number
  from typing import Any, Dict, List, Tuple, Union
  import numpy
  import pandas
  import plotly.graph_objs
  from plotly.basedatatypes import BaseTraceType
  from scipy.stats import gaussian_kde
  from typing_extensions import Literal
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.utils.dataframes import un_numpy
  from deepchecks.utils.distribution.preprocessing import preprocess_2_cat_cols_to_same_bins
  from deepchecks.utils.plot import DEFAULT_DATASET_NAMES, colors
label_desc: Use image node_id 4 for calling a global function with example usage: _create_bars_data_for_mixed_kde_plot(counts, max_kde_value) and returns: unknown