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Carpet Plots in Python

How to make carpet plots in Python with Plotly.


If you're using Dash Enterprise's Data Science Workspaces, you can copy/paste any of these cells into a Workspace Jupyter notebook.
Alternatively, download this entire tutorial as a Jupyter notebook and import it into your Workspace.
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New to Plotly?

Plotly is a free and open-source graphing library for Python. We recommend you read our Getting Started guide for the latest installation or upgrade instructions, then move on to our Plotly Fundamentals tutorials or dive straight in to some Basic Charts tutorials.

Set X and Y Coordinates

To set the x and y coordinates use x and y attributes. If x coordindate values are ommitted a cheater plot will be created. The plot below has a y array specified but requires a and b parameter values before an axis may be plotted.

In [1]:
import plotly.graph_objects as go

fig = go.Figure(go.Carpet(
    y = [2, 3.5, 4, 3, 4.5, 5, 5.5, 6.5, 7.5, 8, 8.5, 10]
))

fig.show()

Add Parameter Values

To save parameter values use the a and b attributes.

In [2]:
import plotly.graph_objects as go

fig = go.Figure(go.Carpet(
    a = [4, 4, 4, 4.5, 4.5, 4.5, 5, 5, 5, 6, 6, 6],
    b = [1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3],
    y = [2, 3.5, 4, 3, 4.5, 5, 5.5, 6.5, 7.5, 8, 8.5, 10]
))

fig.show()

Add A and B axis

Use aaxis or baxis list to make changes to the axes. For a more detailed list of attributes refer to R reference.

In [3]:
import plotly.graph_objects as go

fig = go.Figure(go.Carpet(
    a = [4, 4, 4, 4.5, 4.5, 4.5, 5, 5, 5, 6, 6, 6],
    b = [1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3],
    y = [2, 3.5, 4, 3, 4.5, 5, 5.5, 6.5, 7.5, 8, 8.5, 10],
    aaxis = dict(
        tickprefix = 'a = ',
        ticksuffix = 'm',
        smoothing = 1,
        minorgridcount = 9,
    ),
    baxis = dict(
        tickprefix = 'b = ',
        ticksuffix = 'pa',
        smoothing = 1,
        minorgridcount = 9,
    )
))

fig.show()

Alternate input format

The data arrays x, y may either be specified as one-dimensional arrays of data or as arrays of arrays. If one-dimensional, then x, y, a, and b should all be the same length. If x and y are arrays of arrays, then the length of a should match the inner dimension and the length of b the outer dimension. The plot below represents the same plot as those above.

In [4]:
import plotly.graph_objects as go

fig = go.Figure(go.Carpet(
    a = [4, 4.5, 5, 6],
    b = [1, 2, 3],
    y = [[2, 3, 5.5, 8],
         [3.5, 4.5, 6.5, 8.5],
         [4, 5, 7.5, 10]]
))

fig.show()

Cheater plot layout

The layout of cheater plots is not unique and depends upon the cheaterslope and axis cheatertype parameters. If x is not specified, each row of the x array is constructed based on the the formula a + cheaterslope * b, where a and b are either the value or the integer index of a and b respectively, depending on the corresponding axis cheatertype. Although the layout of the axis below is different than the plots above, it represents the same data as the axes above.

In [5]:
import plotly.graph_objects as go

fig = go.Figure(go.Carpet(
    a = [4, 4.5, 5, 6],
    b = [1, 2, 3],
    y = [[2, 3, 5.5, 8],
         [3.5, 4.5, 6.5, 8.5],
         [4, 5, 7.5, 10]],
    cheaterslope = -5,
    aaxis = dict(cheatertype = 'index'),
    baxis = dict(cheatertype = 'value')
))

fig.show()

Style A and B axis

In [6]:
import plotly.graph_objects as go

fig = go.Figure(go.Carpet(
    a = [4, 4, 4, 4.5, 4.5, 4.5, 5, 5, 5, 6, 6, 6],
    b = [1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, 3],
    y = [2, 3.5, 4, 3, 4.5, 5, 5.5, 6.5, 7.5, 8, 8.5, 10],
    aaxis = dict(
        tickprefix = 'a = ',
        ticksuffix = 'm',
        smoothing = 1,
        minorgridcount = 9,
        minorgridwidth = 0.6,
        minorgridcolor = 'white',
        gridcolor = 'white',
        color = 'white'
    ),
    baxis = dict(
        ticksuffix = 'Pa',
        smoothing = 1,
        minorgridcount = 9,
        minorgridwidth = 0.6,
        gridcolor = 'white',
        minorgridcolor = 'white',
        color = 'white'
    )
))

fig.update_layout(
    plot_bgcolor = 'black',
    paper_bgcolor = 'black',
    xaxis = dict(
        showgrid = False,
        showticklabels = False
    ),
    yaxis = dict(
        showgrid = False,
        showticklabels = False
    )
)

fig.show()

Add Points and Contours

To add points and lines see Carpet Scatter Plots or to add contours see Carpet Contour Plots

Reference

See https://plotly.com/python/reference/carpet/ for more information and chart attribute options!

What About Dash?

Dash is an open-source framework for building analytical applications, with no Javascript required, and it is tightly integrated with the Plotly graphing library.

Learn about how to install Dash at https://dash.plot.ly/installation.

Everywhere in this page that you see fig.show(), you can display the same figure in a Dash application by passing it to the figure argument of the Graph component from the built-in dash_core_components package like this:

import plotly.graph_objects as go # or plotly.express as px
fig = go.Figure() # or any Plotly Express function e.g. px.bar(...)
# fig.add_trace( ... )
# fig.update_layout( ... )

import dash
import dash_core_components as dcc
import dash_html_components as html

app = dash.Dash()
app.layout = html.Div([
    dcc.Graph(figure=fig)
])

app.run_server(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter