class_docstr: Create plots for `PDPIsolate`
  
  Methods
  -------
  plot : generate the plot
  plot_matplotlib : plot using matplotlib
  plot_plotly : plot using plotly
class_docstr_tok: ["Create","plots","for","`","PDPIsolate","`","Methods","--","--","--","-","plot",":","generate","the","plot","plot_matplotlib",":","plot","using","matplotlib","plot_plotly",":","plot","using","plotly"]
code: def _pdp_dist_plot(self, colors, axes, line_axes):
      cmap, _, dark_color = colors
  
      if self.is_numeric and not self.plot_style.to_bins:
          dist_df = self.plot_obj.dist_df
          self._draw_pdp_distplot(dist_df, dark_color, axes)
          vmin, vmax = dist_df.min(), dist_df.max()
          axes.set_xlim(vmin, vmax)
          axes.set_xticks([])
          line_axes.set_xlim(vmin, vmax)
      else:
          self._draw_pdp_countplot(self.plot_obj.count_df, cmap, axes)
  
      axes.set_title(
          "distribution of data points",
          fontdict={
              "family": self.plot_style.font_family,
              "color": self.plot_style.tick["labelcolor"],
          },
          fontsize=self.plot_style.tick["labelsize"],
      )
      axes.tick_params(**self.plot_style.tick)
  
imports: from .utils import _get_string, _to_rgba
  from .styles import _prepare_plot_style, _axes_modify, _display_percentile, _modify_legend_axes, _get_axes_label
  import pandas
  import numpy
  import matplotlib
  import matplotlib.pyplot
  from matplotlib.gridspec import GridSpecFromSubplotSpec
  import copy
  from mpl_toolkits.axes_grid1.inset_locator import inset_axes
  import plotly.graph_objects
  from sklearn.cluster import MiniBatchKMeans, KMeans
  from itertools import cycle
label_desc: Use image node_id 15 for calling the PDPIsolatePlotEngine obj's underlying member method code with example usage: obj._pdp_dist_plot(colors, axes, line_axes) without return types