# `plotly.figure_factory`.create_2d_density¶

`plotly.figure_factory.``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)

deprecated, use instead `plotly.express.density_heatmap()`.

Parameters
• x ((list|array)) – x-axis data for plot generation

• y ((list|array)) – y-axis data for plot generation

• colorscale ((str|tuple|list)) – 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.

• ncontours ((int)) – the number of 2D contours to draw on the plot

• hist_color ((str)) – the color of the plotted histograms

• point_color ((str)) – the color of the scatter points

• point_size ((str)) – the color of the scatter points

• title ((str)) – set the title for the plot

• height ((float)) – the height of the chart

• width ((float)) – the width of the chart

Examples

Example 1: Simple 2D Density Plot

```>>> from plotly.figure_factory import 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
>>> fig.show()
```

Example 2: Using Parameters

```>>> from plotly.figure_factory import 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
>>> fig.show()
```