How to make Ternary plots in Python with Plotly.
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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") fig.show()
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"} )
fig.show()
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': {'text': title, 'font': { '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 }
}
}))
fig.update_layout({
'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 }
}]
})
fig.show()
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
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