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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.
When using Plotly Express, your axes and legend are automatically labelled, and it's easy to override the automation for a customized figure using the labels keyword argument. The title of your figure is up to you though!
Here's a figure with automatic labels and then the same figure with overridden labels. Note the fact that when overriding labels, the axes, legend title and hover labels reflect the specified labels automatically.
import plotly.express as px
df = px.data.iris()
fig = px.scatter(df, x="sepal_length", y="sepal_width", color="species",
title="Automatic Labels Based on Data Frame Column Names")
fig.show()import plotly.express as px
df = px.data.iris()
fig = px.scatter(df, x="sepal_length", y="sepal_width", color="species",
labels={
"sepal_length": "Sepal Length (cm)",
"sepal_width": "Sepal Width (cm)",
"species": "Species of Iris"
},
title="Manually Specified Labels")
fig.show()You can set the figure-wide font with the layout.font attribute, which will apply to all titles and tick labels, but this can be overridden for specific plot items like individual axes and legend titles etc. In the following figure, we set the figure-wide font to Courier New in blue, and then override this for certain parts of the figure.
import plotly.express as px
df = px.data.iris()
fig = px.scatter(df, x="sepal_length", y="sepal_width", color="species",
title="Playing with Fonts")
fig.update_layout(
font_family="Courier New",
font_color="blue",
title_font_family="Times New Roman",
title_font_color="red",
legend_title_font_color="green"
)
fig.update_xaxes(title_font_family="Arial")
fig.show()New in 5.14
Set automargin=True to allow the title to push the figure margins. With yref set to paper, automargin=True expands the margins to make the title visible, but doesn't push outside the container. With yref set to container, automargin=True expands the margins, but the title doesn't overlap with the plot area, tick labels, and axis titles.
import plotly.express as px
df = px.data.gapminder().query("continent == 'Oceania'")
fig = px.line(df, x="year", y="gdpPercap", color="country")
fig.update_layout(
title=dict(text="GDP-per-capita", font=dict(size=50), automargin=True, yref='paper')
)
fig.show()Dash is the best way to build analytical apps in Python using Plotly figures. To run the app below, run pip install dash dash-daq, click "Download" to get the code and run python app.py.
Get started with the official Dash docs and learn how to effortlessly style & deploy apps like this with Dash Enterprise.
from IPython.display import IFrame
snippet_url = 'https://python-docs-dash-snippets.herokuapp.com/python-docs-dash-snippets/'
IFrame(snippet_url + 'figure-labels', width='100%', height=1200)Sign up for Dash Club → Free cheat sheets plus updates from Chris Parmer and Adam Schroeder delivered to your inbox every two months. Includes tips and tricks, community apps, and deep dives into the Dash architecture. Join now.
When using graph objects rather than Plotly Express, you will need to explicitly label traces and axes:
import plotly.graph_objects as go
fig = go.Figure()
fig.add_trace(go.Scatter(
x=[0, 1, 2, 3, 4, 5, 6, 7, 8],
y=[0, 1, 2, 3, 4, 5, 6, 7, 8],
name="Name of Trace 1" # this sets its legend entry
))
fig.add_trace(go.Scatter(
x=[0, 1, 2, 3, 4, 5, 6, 7, 8],
y=[1, 0, 3, 2, 5, 4, 7, 6, 8],
name="Name of Trace 2"
))
fig.update_layout(
title="Plot Title",
xaxis_title="X Axis Title",
yaxis_title="Y Axis Title",
legend_title="Legend Title",
font=dict(
family="Courier New, monospace",
size=18,
color="RebeccaPurple"
)
)
fig.show()New in 5.22
You can configure a variant, style, and weight on layout.font. Here, we set the font variant to small-caps.
import plotly.graph_objects as go
from plotly import data
df = data.iris()
setosa_df = df[df["species"] == "setosa"]
versicolor_df = df[df["species"] == "versicolor"]
virginica_df = df[df["species"] == "virginica"]
fig = go.Figure(
data=[
go.Scatter(
x=setosa_df["sepal_width"],
y=setosa_df["sepal_length"],
mode="markers",
name="setosa",
),
go.Scatter(
x=versicolor_df["sepal_width"],
y=versicolor_df["sepal_length"],
mode="markers",
name="versicolor",
),
go.Scatter(
x=virginica_df["sepal_width"],
y=virginica_df["sepal_length"],
mode="markers",
name="virginica",
),
],
layout=go.Layout(
title="Plot Title",
xaxis=dict(title="X Axis Title"),
yaxis=dict(title="Y Axis Title"),
legend=dict(title="Legend Title"),
font=dict(
family="Courier New, monospace",
size=18,
color="RebeccaPurple",
variant="small-caps",
)
)
)
fig.show()The configuration of the legend is discussed in detail in the Legends page.
The following example shows how to align the plot title in layout.title. x sets the x position with respect to xref from "0" (left) to "1" (right), and y sets the y position with respect to yref from "0" (bottom) to "1" (top). Moreover, you can define xanchor to left,right, or center for setting the title's horizontal alignment with respect to its x position, and/or yanchor to top, bottom, or middle for setting the title's vertical alignment with respect to its y position.
import plotly.graph_objects as go
fig = go.Figure(go.Scatter(
y=[3, 1, 4],
x=["Mon", "Tue", "Wed"]))
fig.update_layout(
title={
'text': "Plot Title",
'y':0.9,
'x':0.5,
'xanchor': 'center',
'yanchor': 'top'})
fig.show()See https://plotly.com/python/reference/layout/ for more information!