Setting Graph Size in Python

How to manipulate the graph size, margins and background color.

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.

Adjusting Height, Width, & Margins 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.

In [1]:

import plotly.express as px

df = px.data.tips()
fig = px.scatter(df, x="total_bill", y="tip", facet_col="sex",
                 width=800, height=400)

fig.update_layout(
    margin=dict(l=20, r=20, t=20, b=20),
    paper_bgcolor="LightSteelBlue",
)

fig.show()

Adjusting graph size with Dash¶

Dash is the best way to build analytical apps in Python using Plotly figures. To run the app below, run pip install dash, 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.

Out[2]:

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Adjusting Height, Width, & Margins With Graph Objects¶

Graph objects are the low-level building blocks of figures which you can use instead of Plotly Express for greater control.

In [3]:

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]
))

fig.update_layout(
    autosize=False,
    width=500,
    height=500,
    margin=dict(
        l=50,
        r=50,
        b=100,
        t=100,
        pad=4
    ),
    paper_bgcolor="LightSteelBlue",
)

fig.show()

Automatically Adjust Margins¶

Set automargin to True and Plotly will automatically increase the margin size to prevent ticklabels from being cut off or overlapping with axis titles.

In [4]:

import plotly.graph_objects as go


fig = go.Figure()

fig.add_trace(go.Bar(
    x=["Apples", "Oranges", "Watermelon", "Pears"],
    y=[3, 2, 1, 4]
))

fig.update_layout(
    autosize=False,
    width=500,
    height=500,
    yaxis=dict(
        title=dict(
            text="Y-axis Title",
            font=dict(
                size=30
            )
        ),
        ticktext=["Very long label", "long label", "3", "label"],
        tickvals=[1, 2, 3, 4],
        tickmode="array",
    )
)

fig.update_yaxes(automargin=True)

fig.show()

Automatically Adjust Specific Margins¶

New in 5.10

You can also set automargin for specific sides of the figure. Here, we set automargin on the left and top of the figure.

In [5]:

import plotly.graph_objects as go


fig = go.Figure()

fig.add_trace(go.Bar(
    x=["Apples", "Oranges", "Watermelon", "Pears"],
    y=[3, 2, 1, 4]
))

fig.update_layout(
    autosize=False,
    width=500,
    height=500,
    yaxis=dict(
        title=dict(
            text="Y-axis Title",
            font=dict(
                size=30
            )
        ),
        ticktext=["Very long label", "long label", "3", "label"],
        tickvals=[1, 2, 3, 4],
        tickmode="array",
    )
)

fig.update_yaxes(automargin='left+top')

fig.show()

Setting a Minimum Plot Size with Automargins¶

New in 5.11

To set a minimum width and height for a plot to be after automargin is applied, use minreducedwidth and minreducedheight. Here we set both to 250.

In [6]:

import plotly.graph_objects as go


fig = go.Figure()

fig.add_trace(go.Bar(
    x=["Apples", "Oranges", "Watermelon", "Pears"],
    y=[3, 2, 1, 4]
))

fig.update_layout(
    autosize=False,
    minreducedwidth=250,
    minreducedheight=250,
    width=450,
    height=450,
    yaxis=dict(
        title=dict(
            text="Y-axis Title",
            font=dict(
                size=30
            )
        ),
        ticktext=["Label", "Very long label", "Other label", "Very very long label"],
        tickvals=[1, 2, 3, 4],
        tickmode="array",
    )
)


fig.show()

Reference¶

See https://plotly.com/python/reference/layout/ 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_server(debug=True, use_reloader=False)  # Turn off reloader if inside Jupyter