docstr: Adapts the color scale to the distribution of points
  Parameters
  ----------
  values: 1 column pd.DataFrame
      values ​​whose quantiles must be calculated
docstr_tok: ["Adapts","the","color","scale","to","the","distribution","of","points","Parameters","--","--","--","--","--","values",":","1","column","pd.DataFrame","values","\u200b\u200bwhose","quantiles","must","be","calculated"]
code: def tuning_colorscale(self, values):
      """Adapts the color scale to the distribution of points
      Parameters
      ----------
      values: 1 column pd.DataFrame
          values ​​whose quantiles must be calculated
      """
      desc_df = values.describe(
          percentiles=np.arange(0.1, 1, 0.1).tolist()
      )
      min_pred, max_init = list(desc_df.loc[["min", "max"]].values)
      desc_pct_df = (
          desc_df.loc[~desc_df.index.isin(["count", "mean", "std"])]
          - min_pred
      ) / (max_init - min_pred)
      color_scale = list(
          map(
              list,
              (
                  zip(
                      desc_pct_df.values.flatten(),
                      self._style_dict["init_contrib_colorscale"],
                  )
              ),
          )
      )
      return color_scale
  
imports: from category_encoders import OrdinalEncoder
  import copy
  import itertools
  import matplotlib.pyplot
  import numpy
  import pandas
  from plotly import graph_objs
  from plotly.offline import plot
  from plotly.subplots import make_subplots
  from sklearn.manifold import MDS
  from shapash import SmartExplainer
  from shapash.style.style_utils import colors_loading, select_palette, define_style
label_desc: Use image node_id 2 for calling the Consistency obj's underlying member method code with example usage: obj.tuning_colorscale(values) and returns: color_scale