code: def kde(
      data,
      bw,
      cmap="hot",
      method="hist",
      scaling="sqrt",
      alpha=220,
      cut_below=None,
      clip_above=None,
      binsize=1,
      cmap_levels=10,
      show_colorbar=False,
  ):
      """
      Kernel density estimation visualization
  
      :param data: data access object
      :param bw: kernel bandwidth (in screen coordinates)
      :param cmap: colormap
      :param method: if kde use KDEMultivariate from statsmodel, which provides a more accurate but much slower estimation.
          If hist, estimates density applying gaussian smoothing on a 2D histogram, which is much faster but less accurate
      :param scaling: colorscale, lin log or sqrt
      :param alpha: color alpha
      :param cut_below: densities below cut_below are not drawn
      :param clip_above: defines the max value for the colorscale
      :param binsize: size of the bins for hist estimator
      :param cmap_levels: discretize colors into cmap_levels levels
      :param show_colorbar: show colorbar
      """
      from geoplotlib.layers import KDELayer
  
      _global_config.layers.append(
          KDELayer(
              data,
              bw,
              cmap,
              method,
              scaling,
              alpha,
              cut_below,
              clip_above,
              binsize,
              cmap_levels,
              show_colorbar,
          )
      )
  
imports: import base64
  import traceback
  import pyglet
  from geoplotlib.core import GeoplotlibApp
  from core import FONT_NAME
label_desc: Use image node_id 13 for calling a global function with example usage: kde(data, bw, cmap, method, scaling, alpha, cut_below, clip_above, binsize, cmap_levels, show_colorbar) without return types