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Ternary Plots in Python

How to make Ternary plots in Python with Plotly.

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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.

Ternary Plots

A ternary plot depicts the ratios of three variables as positions in an equilateral triangle.

Ternary scatter plot 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.

Here we use px.scatter_ternary to visualize the three-way split between the three major candidates in a municipal election.

In [1]:
import plotly.express as px
df = px.data.election()
fig = px.scatter_ternary(df, a="Joly", b="Coderre", c="Bergeron")

We can scale and color the markers to produce a ternary bubble chart.

In [2]:
import plotly.express as px
df = px.data.election()
fig = px.scatter_ternary(df, a="Joly", b="Coderre", c="Bergeron", hover_name="district",
    color="winner", size="total", size_max=15,
    color_discrete_map = {"Joly": "blue", "Bergeron": "green", "Coderre":"red"} )

Ternary scatter plot with Plotly Graph Objects

In [3]:
import plotly.graph_objects as go

rawData = [
    {'journalist':75,'developer':25,'designer':0,'label':'point 1'},
    {'journalist':70,'developer':10,'designer':20,'label':'point 2'},
    {'journalist':75,'developer':20,'designer':5,'label':'point 3'},
    {'journalist':5,'developer':60,'designer':35,'label':'point 4'},
    {'journalist':10,'developer':80,'designer':10,'label':'point 5'},
    {'journalist':10,'developer':90,'designer':0,'label':'point 6'},
    {'journalist':20,'developer':70,'designer':10,'label':'point 7'},
    {'journalist':10,'developer':20,'designer':70,'label':'point 8'},
    {'journalist':15,'developer':5,'designer':80,'label':'point 9'},
    {'journalist':10,'developer':10,'designer':80,'label':'point 10'},
    {'journalist':20,'developer':10,'designer':70,'label':'point 11'},

def makeAxis(title, tickangle):
    return {
      'title': title,
      'titlefont': { 'size': 20 },
      'tickangle': tickangle,
      'tickfont': { 'size': 15 },
      'tickcolor': 'rgba(0,0,0,0)',
      'ticklen': 5,
      'showline': True,
      'showgrid': True

fig = go.Figure(go.Scatterternary({
    'mode': 'markers',
    'a': [i for i in map(lambda x: x['journalist'], rawData)],
    'b': [i for i in map(lambda x: x['developer'], rawData)],
    'c': [i for i in map(lambda x: x['designer'], rawData)],
    'text': [i for i in map(lambda x: x['label'], rawData)],
    'marker': {
        'symbol': 100,
        'color': '#DB7365',
        'size': 14,
        'line': { 'width': 2 }

    'ternary': {
        'sum': 100,
        'aaxis': makeAxis('Journalist', 0),
        'baxis': makeAxis('<br>Developer', 45),
        'caxis': makeAxis('<br>Designer', -45)
    'annotations': [{
      'showarrow': False,
      'text': 'Simple Ternary Plot with Markers',
        'x': 0.5,
        'y': 1.3,
        'font': { 'size': 15 }



See function reference for px.(scatter_ternary) or https://plotly.com/python/reference/scatterternary/ 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([

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