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 _draw_pdp_countplot(self, data, cmap, axes):
      count_norm = data["count_norm"].values
      norm = mpl.colors.Normalize(vmin=0, vmax=np.max(count_norm))
      _modify_legend_axes(axes, self.plot_style.font_family)
  
      xticks = data["x"].values
      axes.imshow(
          np.expand_dims(count_norm, 0),
          aspect="auto",
          cmap=cmap,
          norm=norm,
          alpha=self.plot_style.dist["fill_alpha"],
          extent=(np.min(xticks) - 0.5, np.max(xticks) + 0.5, 0, 0.5),
      )
  
      for i, v in enumerate(count_norm):
          text_color = "black"
          if v >= np.max(count_norm) * 0.5:
              text_color = "white"
          axes.text(
              xticks[i],
              0.25,
              round(v, 3),
              ha="center",
              va="center",
              color=text_color,
              fontdict={
                  "family": self.plot_style.font_family,
                  "fontsize": self.plot_style.dist["font_size"],
              },
          )
  
      axes.set_xticks(xticks[:-1] + 0.5, minor=True)
      axes.grid(which="minor", color="w", linestyle="-", linewidth=1.5)
      axes.tick_params(which="minor", bottom=False, left=False)
  
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 14 for calling the PDPIsolatePlotEngine obj's underlying member method code with example usage: obj._draw_pdp_countplot(data, cmap, axes) without return types