text: from __future__ import absolute_import
  
  from numbers import Number
  
  from plotly import exceptions
  from plotly.figure_factory import utils
  from plotly.graph_objs import graph_objs
  
  
  def make_linear_colorscale(colors):
      """
      Makes a list of colors into a colorscale-acceptable form
  
      For documentation regarding to the form of the output, see
      https://plot.ly/python/reference/#mesh3d-colorscale
      """
      scale = 1. / (len(colors) - 1)
      return [[i * scale, color] for i, color in enumerate(colors)]
  
  
  def create_2d_density(x, y, colorscale='Earth', ncontours=20,
                        hist_color=(0, 0, 0.5), point_color=(0, 0, 0.5),
                        point_size=2, title='2D Density Plot',
                        height=600, width=600):
      """
      Returns figure for a 2D density plot
  
      :param (list|array) x: x-axis data for plot generation
      :param (list|array) y: y-axis data for plot generation
      :param (str|tuple|list) colorscale: either a plotly scale name, an rgb
          or hex color, a color tuple or a list or tuple of colors. An rgb
          color is of the form 'rgb(x, y, z)' where x, y, z belong to the
          interval [0, 255] and a color tuple is a tuple of the form
          (a, b, c) where a, b and c belong to [0, 1]. If colormap is a
          list, it must contain the valid color types aforementioned as its
          members.
      :param (int) ncontours: the number of 2D contours to draw on the plot
      :param (str) hist_color: the color of the plotted histograms
      :param (str) point_color: the color of the scatter points
      :param (str) point_size: the color of the scatter points
      :param (str) title: set the title for the plot
      :param (float) height: the height of the chart
      :param (float) width: the width of the chart
  
      Example 1: Simple 2D Density Plot
      ```
      import plotly.plotly as py
      from plotly.figure_factory create_2d_density
  
      import numpy as np
  
      # Make data points
      t = np.linspace(-1,1.2,2000)
      x = (t**3)+(0.3*np.random.randn(2000))
      y = (t**6)+(0.3*np.random.randn(2000))
  
      # Create a figure
      fig = create_2D_density(x, y)
  
      # Plot the data
      py.iplot(fig, filename='simple-2d-density')
      ```
  
      Example 2: Using Parameters
      ```
      import plotly.plotly as py
      from plotly.figure_factory create_2d_density
  
      import numpy as np
  
      # Make data points
      t = np.linspace(-1,1.2,2000)
      x = (t**3)+(0.3*np.random.randn(2000))
      y = (t**6)+(0.3*np.random.randn(2000))
  
      # Create custom colorscale
      colorscale = ['#7A4579', '#D56073', 'rgb(236,158,105)',
                    (1, 1, 0.2), (0.98,0.98,0.98)]
  
      # Create a figure
      fig = create_2D_density(
          x, y, colorscale=colorscale,
          hist_color='rgb(255, 237, 222)', point_size=3)
  
      # Plot the data
      py.iplot(fig, filename='use-parameters')
      ```
      """
  
      # validate x and y are filled with numbers only
      for array in [x, y]:
          if not all(isinstance(element, Number) for element in array):
              raise exceptions.PlotlyError(
                  "All elements of your 'x' and 'y' lists must be numbers."
              )
  
      # validate x and y are the same length
      if len(x) != len(y):
          raise exceptions.PlotlyError(
              "Both lists 'x' and 'y' must be the same length."
          )
  
      colorscale = utils.validate_colors(colorscale, 'rgb')
      colorscale = make_linear_colorscale(colorscale)
  
      # validate hist_color and point_color
      hist_color = utils.validate_colors(hist_color, 'rgb')
      point_color = utils.validate_colors(point_color, 'rgb')
  
      trace1 = graph_objs.Scatter(
          x=x, y=y, mode='markers', name='points',
          marker=dict(
              color=point_color[0],
              size=point_size,
              opacity=0.4
          )
      )
      trace2 = graph_objs.Histogram2dcontour(
          x=x, y=y, name='density', ncontours=ncontours,
          colorscale=colorscale, reversescale=True, showscale=False
      )
      trace3 = graph_objs.Histogram(
          x=x, name='x density',
          marker=dict(color=hist_color[0]), yaxis='y2'
      )
      trace4 = graph_objs.Histogram(
          y=y, name='y density',
          marker=dict(color=hist_color[0]), xaxis='x2'
      )
      data = [trace1, trace2, trace3, trace4]
  
      layout = graph_objs.Layout(
          showlegend=False,
          autosize=False,
          title=title,
          height=height,
          width=width,
          xaxis=dict(
              domain=[0, 0.85],
              showgrid=False,
              zeroline=False
          ),
          yaxis=dict(
              domain=[0, 0.85],
              showgrid=False,
              zeroline=False
          ),
          margin=dict(
              t=50
          ),
          hovermode='closest',
          bargap=0,
          xaxis2=dict(
              domain=[0.85, 1],
              showgrid=False,
              zeroline=False
          ),
          yaxis2=dict(
              domain=[0.85, 1],
              showgrid=False,
              zeroline=False
          )
      )
  
      fig = graph_objs.Figure(data=data, layout=layout)
      return fig
  