Plotly.Express.Density

“A density contour refers to a 2-dimensional histogram resembling a contour plot but is computed by grouping a set of data points as defined by x and y coordinates and applying an aggregate function.

Let’s discuss how to create a density contour plot using Plotly express.”

Function Syntax

The function syntax is as shown:

plotly.express.density_contour(data_frame=None, x=None, y=None, z=None, color=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_discrete_sequence=None, color_discrete_map=None, marginal_x=None, marginal_y=None, trendline=None, trendline_options=None, trendline_color_override=None, trendline_scope='trace', log_x=False, log_y=False, range_x=None, range_y=None, histfunc=None, histnorm=None, nbinsx=None, nbinsy=None, text_auto=False, title=None, template=None, width=None, height=None)

Function parameters:

data_frame – specifies the data containing the columns used in the plot.
x – defines the values used to position the marks along the x-axis.
y – sets the values used to position the marks along the y axis.
z – defines the values used to position the marks along the z-axis.
color – defines the values used to assign a unique color to the marks of the plot.
orientation – defines the orientation of the plot.
title – sets the title for the figure.
template – defines the plotly template used in the figure.
width/height – sets the width and height of the figure in pixels.

Practical Example

The code below shows how to create a density contour plot using Plotly Express and the iris data.

import plotly.express as px
df = px.data.tips()
fig = px.density_contour(df, x='total_bill', y='tip')
fig.show()

Output:

Color Contours

To color the contours, you can specify the color parameter as shown in the example below:

import plotly.express as px
df = px.data.tips()
fig = px.density_contour(df, x='total_bill', y='tip', color='sex')
fig.show()

The resulting figure is shown below:

Facetted Density Contour

You can also create a facetted contour plot by setting the facet_col parameter as shown:

import plotly.express as px
df = px.data.tips()
fig = px.density_contour(df, x='total_bill', y='tip', facet_col='sex', color='smoker')
fig.show()

This should display a plot as shown:

Showing Labels

To display the labels in the plot, we can set the contours_showlabels.

fig = px.density_contour(df, x='total_bill', y='tip', facet_col='sex', color='smoker')
fig.update_traces(contours_showlabels=True)
fig.show()

The code above shows the return of the contour with the data labels included.

Continuously Colored Contour

If you wish to create a contour that is continuously colored, you can set he contours_coloring parameter to fill as:

fig = px.density_contour(df, x='total_bill', y='tip', facet_col='sex', color='smoker')
fig.update_traces(contours_showlabels=True, contours_coloring='fill')
fig.show()

The resulting figure is as shown:

Specifying Aggregate Function

You can also specify an aggregate function to the density contour by setting the z parameter and the histfunc parameters.

An example code is as shown:

import plotly.express as px
df = px.data.iris()
fig = px.density_contour(df, x='petal_length', y='petal_width', z='sepal_length', histfunc='max')
fig.show()

The code above will return a density contour as shown:

Conclusion

This article explores the density_contour() function, which allows you to create 2d histogram plots.

Happy coding!!

Plotly.Express.Density_contour