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Legends in Python

How to configure and style the legend in Plotly with Python.

Show Legend

By default the legend is displayed on Plotly charts with multiple traces.

In [1]:
import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[1, 2, 3, 4, 5],
))

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[5, 4, 3, 2, 1],
))

fig.show()

Add showlegend=True to the layout object to display the legend on a plot with a single trace.

In [2]:
import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[1, 2, 3, 4, 5],
))

fig.update_layout(showlegend=True)

fig.show()

Hide Legend

In [3]:
import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[1, 2, 3, 4, 5],
))

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[5, 4, 3, 2, 1],
))

fig.update_layout(showlegend=False)

fig.show()

Hide Legend Entries

In [4]:
import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[1, 2, 3, 4, 5],
    showlegend=False
))


fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[5, 4, 3, 2, 1],
))

fig.update_layout(showlegend=True)

fig.show()

Legend Names

In [5]:
import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[1, 2, 3, 4, 5],
    name="Positive"
))

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[5, 4, 3, 2, 1],
    name="Negative"
))

fig.show()

Legend titles

In [6]:
import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[1, 2, 3, 4, 5],
    name="Increasing"
))

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[5, 4, 3, 2, 1],
    name="Decreasing"
))

fig.update_layout(legend_title='<b> Trend </b>')
fig.show()

Horizontal Legend

In [7]:
import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[1, 2, 3, 4, 5],
))

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[5, 4, 3, 2, 1],
))

fig.update_layout(legend_orientation="h")

fig.show()

Legend Position

In [8]:
import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[1, 2, 3, 4, 5],
))

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[5, 4, 3, 2, 1],
))

fig.update_layout(legend=dict(x=-.1, y=1.2))

fig.show()

Style Legend

In [9]:
import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[1, 2, 3, 4, 5],
))

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[5, 4, 3, 2, 1],
))

fig.update_layout(
    legend=dict(
        x=0,
        y=1,
        traceorder="normal",
        font=dict(
            family="sans-serif",
            size=12,
            color="black"
        ),
        bgcolor="LightSteelBlue",
        bordercolor="Black",
        borderwidth=2
    )
)

fig.show()

Size of Legend Items

In this example itemsizing attribute determines the legend items symbols remain constant, regardless of how tiny/huge the bubbles would be in the graph.

In [10]:
import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[1, 2, 3, 4, 5],
    mode='markers',
    marker={'size':10}
))

fig.add_trace(go.Scatter(
    x=[1, 2, 3, 4, 5],
    y=[5, 4, 3, 2, 1],
    mode='markers',
    marker={'size':100}
))

fig.update_layout(legend= {'itemsizing': 'constant'})

fig.show()

Grouped Legend

In [11]:
import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(
    x=[1, 2, 3],
    y=[2, 1, 3],
    legendgroup="group",  # this can be any string, not just "group"
    name="first legend group",
    mode="markers",
    marker=dict(color="Crimson", size=10)
))

fig.add_trace(go.Scatter(
    x=[1, 2, 3],
    y=[2, 2, 2],
    legendgroup="group",
    name="first legend group - average",
    mode="lines",
    line=dict(color="Crimson")
))

fig.add_trace(go.Scatter(
    x=[1, 2, 3],
    y=[4, 9, 2],
    legendgroup="group2",
    name="second legend group",
    mode="markers",
    marker=dict(color="MediumPurple", size=10)
))

fig.add_trace(go.Scatter(
    x=[1, 2, 3],
    y=[5, 5, 5],
    legendgroup="group2",
    name="second legend group - average",
    mode="lines",
    line=dict(color="MediumPurple")
))

fig.show()

You can also hide entries in grouped legends:

In [12]:
import plotly.graph_objects as go

fig = go.Figure()

fig.add_trace(go.Scatter(
    x=[1, 2, 3],
    y=[2, 1, 3],
    legendgroup="group",  # this can be any string, not just "group"
    name="first legend group",
    mode="markers",
    marker=dict(color="Crimson", size=10)
))

fig.add_trace(go.Scatter(
    x=[1, 2, 3],
    y=[2, 2, 2],
    legendgroup="group",
    name="first legend group - average",
    mode="lines",
    line=dict(color="Crimson"),
    showlegend=False,
))

fig.add_trace(go.Scatter(
    x=[1, 2, 3],
    y=[4, 9, 2],
    legendgroup="group2",
    name="second legend group",
    mode="markers",
    marker=dict(color="MediumPurple", size=10)
))

fig.add_trace(go.Scatter(
    x=[1, 2, 3],
    y=[5, 5, 5],
    legendgroup="group2",
    name="second legend group - average",
    mode="lines",
    line=dict(color="MediumPurple"),
    showlegend=False,
))

fig.show()

Legend items for continuous fields (2D and 3D)

Traces corresponding to 2D fields (e.g. go.Heatmap, go.Histogram2d) or 3D fields (e.g. go.Isosurface, go.Volume, go.Cone) can also appear in the legend. They come with legend icons corresponding to each trace type, which are colored using the same colorscale as the trace.

The example below explores a vector field using several traces. Note that you can click on legend items to hide or to select (with a double click) a specific trace. This will make the exploration of your data easier!

In [13]:
import numpy as np
import plotly.graph_objects as go

# Define vector and scalar fields
x, y, z = np.mgrid[0:1:8j, 0:1:8j, 0:1:8j]
u =    np.sin(np.pi*x) * np.cos(np.pi*z)
v = -2*np.sin(np.pi*y) * np.cos(2*np.pi*z)
w = np.cos(np.pi*x)*np.sin(np.pi*z) + np.cos(np.pi*y)*np.sin(2*np.pi*z)
magnitude = np.sqrt(u**2 + v**2 + w**2)
mask1 = np.logical_and(y>=.4, y<=.6)
mask2 = y>.6

fig = go.Figure(go.Isosurface(
                      x=x.ravel(), y=y.ravel(), z=z.ravel(),
                      value=magnitude.ravel(),
                      isomin=1.9, isomax=1.9,
                      colorscale="BuGn",
                      name='isosurface'))


fig.add_trace(go.Cone(x=x[mask1], y=y[mask1], z=z[mask1],
                      u=u[mask1], v=v[mask1], w=w[mask1],
                      colorscale="Blues",
                      name='cones'
))
fig.add_trace(go.Streamtube(
                      x=x[mask2], y=y[mask2], z=z[mask2],
                      u=u[mask2], v=v[mask2], w=w[mask2],
                      colorscale="Reds",
                      name='streamtubes'
))
# Update all traces together
fig.update_traces(showlegend=True, showscale=False)
fig.update_layout(width=600, title_text='Exporation of a vector field using several traces')
fig.show()

Reference

See https://plot.ly/python/reference/#layout-legend for more information!