code: def density_heatmap(
      data_frame=None,
      x=None,
      y=None,
      z=None,
      facet_row=None,
      facet_col=None,
      facet_col_wrap=0,
      facet_row_spacing=None,
      facet_col_spacing=None,
      hover_name=None,
      hover_data=None,
      animation_frame=None,
      animation_group=None,
      category_orders=None,
      labels=None,
      orientation=None,
      color_continuous_scale=None,
      range_color=None,
      color_continuous_midpoint=None,
      marginal_x=None,
      marginal_y=None,
      opacity=None,
      log_x=False,
      log_y=False,
      range_x=None,
      range_y=None,
      histfunc=None,
      histnorm=None,
      nbinsx=None,
      nbinsy=None,
      title=None,
      template=None,
      width=None,
      height=None,
  ):
      """
      In a density heatmap, rows of `data_frame` are grouped together into
      colored rectangular tiles to visualize the 2D distribution of an
      aggregate function `histfunc` (e.g. the count or sum) of the value `z`.
      """
      return make_figure(
          args=locals(),
          constructor=go.Histogram2d,
          trace_patch=dict(
              histfunc=histfunc,
              histnorm=histnorm,
              nbinsx=nbinsx,
              nbinsy=nbinsy,
              xbingroup="x",
              ybingroup="y",
          ),
      )
  
imports: from ._core import make_figure
  from ._doc import make_docstring
  import plotly.graph_objs
label_desc: Use image node_id 3 for calling a global function with example usage: density_heatmap(data_frame, x, y, z, facet_row, facet_col, facet_col_wrap, facet_row_spacing, facet_col_spacing, hover_name, hover_data, animation_frame, animation_group, category_orders, labels, orientation, color_continuous_scale, range_color, color_continuous_midpoint, marginal_x, marginal_y, opacity, log_x, log_y, range_x, range_y, histfunc, histnorm, nbinsx, nbinsy, title, template, width, height) and returns: make_figure