Radar Charts in Python

How to make radar charts in Python with Plotly.


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A Radar Chart (also known as a spider plot or star plot) displays multivariate data in the form of a two-dimensional chart of quantitative variables represented on axes originating from the center. The relative position and angle of the axes is typically uninformative. It is equivalent to a parallel coordinates plot with the axes arranged radially.

For a Radar Chart, use a polar chart with categorical angular variables, with px.line_polar, or with go.Scatterpolar. See more examples of polar charts.

Radar Chart with Plotly Express

Plotly Express is the easy-to-use, high-level interface to Plotly, which operates on a variety of types of data and produces easy-to-style figures.

Use line_close=True for closed lines.

In [1]:
import plotly.express as px
import pandas as pd
df = pd.DataFrame(dict(
    r=[1, 5, 2, 2, 3],
    theta=['processing cost','mechanical properties','chemical stability',
           'thermal stability', 'device integration']))
fig = px.line_polar(df, r='r', theta='theta', line_close=True)
fig.show()
processing costmechanical propertieschemical stabilitythermal stabilitydevice integration012345

For a filled line in a Radar Chart, update the figure created with px.line_polar with fig.update_traces.

In [2]:
import plotly.express as px
import pandas as pd
df = pd.DataFrame(dict(
    r=[1, 5, 2, 2, 3],
    theta=['processing cost','mechanical properties','chemical stability',
           'thermal stability', 'device integration']))
fig = px.line_polar(df, r='r', theta='theta', line_close=True)
fig.update_traces(fill='toself')
fig.show()
processing costmechanical propertieschemical stabilitythermal stabilitydevice integration012345

Basic Radar Chart with go.Scatterpolar

In [3]:
import plotly.graph_objects as go

fig = go.Figure(data=go.Scatterpolar(
  r=[1, 5, 2, 2, 3],
  theta=['processing cost','mechanical properties','chemical stability', 'thermal stability',
           'device integration'],
  fill='toself'
))

fig.update_layout(
  polar=dict(
    radialaxis=dict(
      visible=True
    ),
  ),
  showlegend=False
)

fig.show()
processing costmechanical propertieschemical stabilitythermal stabilitydevice integration012345

Multiple Trace Radar Chart

In [4]:
import plotly.graph_objects as go

categories = ['processing cost','mechanical properties','chemical stability',
              'thermal stability', 'device integration']

fig = go.Figure()

fig.add_trace(go.Scatterpolar(
      r=[1, 5, 2, 2, 3],
      theta=categories,
      fill='toself',
      name='Product A'
))
fig.add_trace(go.Scatterpolar(
      r=[4, 3, 2.5, 1, 2],
      theta=categories,
      fill='toself',
      name='Product B'
))

fig.update_layout(
  polar=dict(
    radialaxis=dict(
      visible=True,
      range=[0, 5]
    )),
  showlegend=False
)

fig.show()
processing costmechanical propertieschemical stabilitythermal stabilitydevice integration012345

Reference

See function reference for px.(line_polar) or https://plotly.com/python/reference/scatterpolar/ 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( ... )

from dash import Dash, dcc, html

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

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