5 Best Ways to Change the Size of a Dash Graph in Python Plotly

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💡 Problem Formulation: When working with Plotly in Dash, a common requirement is to adjust the dimensions of your graphs to fit a certain design aesthetic or to enhance data visualization. For example, you may have an input graph that’s 800×600 pixels but need to change its size to 1024×768 pixels.

Method 1: Setting Figure Layout Properties

Plotly’s Dash allows you to specify the size of the graph directly within the layout property of a figure object. By setting the width and height in the layout dictionary, the dimensions of the chart will be adjusted accordingly.

Here’s an example:

import plotly.graph_objs as go
from dash import Dash, dcc

app = Dash(__name__)
fig = go.Figure(
    data=[go.Bar(y=[1, 3, 2])],
    layout=title='My Graph', width=1024, height=768)
)
app.layout = dcc.Graph(figure=fig)

if __name__ == '__main__':
    app.run_server(debug=True)

Output: A Dash application displaying a bar graph resized to 1024×768 pixels.

In the provided snippet, we create a simple bar graph and set the width and height in the layout. This determines the displayed size of the graph within the Dash app, which is then visualized using dcc.Graph.

Method 2: CSS Styling

Another flexible method to change the size of the graph is by using Cascading Style Sheets (CSS). You can define a CSS class with the desired dimensions and apply it to the dcc.Graph component.

Here’s an example:

app.layout = html.Div([
    dcc.Graph(
        id='example-graph',
        figure=fig,
        className='custom-graph-class'
    )
])

# Assume 'custom-graph-class' is defined in a linked CSS file with the following:
# .custom-graph-class { width: 1024px; height: 768px; }

Output: A Dash application with a graph styled according to the custom CSS class ‘custom-graph-class’ at 1024×768 pixels.

Within the Dash layout, we assign the custom CSS class to the dcc.Graph component. This class should be defined in an external or internal stylesheet, setting the width and height of the graph to our desired dimensions.

Method 3: Inline Styling

For quick changes without the need for external stylesheets, inline styling is a convenient method to adjust graph size. Directly pass a style dictionary with specified width and height to the dcc.Graph component.

Here’s an example:

app.layout = html.Div([
    dcc.Graph(
        id='example-graph',
        figure=fig,
        style={'width': '1024px', 'height': '768px'}
    )
])

Output: The graph is rendered within the Dash app at the specified inline styles of 1024×768 pixels.

The inline style attribute allows the dimensions to be adjusted immediately in the layout. It’s a straightforward method that doesn’t require any external setups but is less scalable than using a stylesheet.

Method 4: Using Plotly Figure Objects

Modifying the dimensions of your graph can also be accomplished through Plotly Figure objects. You can directly instantiate a Figure object with a specified layout size before passing it into the Dash app.

Here’s an example:

fig = go.Figure(data=[go.Scatter(x=[1, 2, 3], y=[4, 5, 6])])
fig.update_layout(width=1024, height=768)

app.layout = dcc.Graph(
    id='example-graph',
    figure=fig
)

Output: A Dash application showing a scatter plot with a specified size of 1024×768 pixels.

This snippet demonstrates the use of the update_layout method on a Plotly figure object, which allows for finer control over the graph’s appearance, including the dimensions, before integrating it within a Dash component.

Bonus One-Liner Method 5: Adjusting Size in Figure Instantiation

For the quickest inline solution, adjust your graph’s dimensions directly upon the instantiation of the figure object. This one-liner method is efficient when you’re creating a new figure and know the size ahead of time.

Here’s an example:

fig = go.Figure(data=[go.Bar(x=[1, 2, 3], y=[3, 1, 2])], layout=go.Layout(width=1024, height=768))
app.layout = dcc.Graph(figure=fig)

Output: An immediately created bar chart with customized dimensions of 1024×768 pixels in a Dash application.

The example shows the direct setting of the width and height in the layout argument during the creation of a figure. This one-liner approach skips additional steps and is very concise.

Summary/Discussion

  • Method 1: Setting Figure Layout Properties. This method is directly tied to the plotly figure, making it straightforward. However, it may not be flexible enough for dynamic sizing scenarios.
  • Method 2: CSS Styling. This approach is best for maintaining a consistent look across various components and allows for responsive designs. The drawback is that it requires an understanding of CSS and possibly more setup.
  • Method 3: Inline Styling. Inline styling is quick and easy to implement but is less maintainable and scalable than external CSS styling.
  • Method 4: Using Plotly Figure Objects. Using figure objects provides extensive control over the graph layout, but might be overkill for simple size adjustments.
  • Method 5: Bonus One-Liner. The one-liner method is the most straightforward but offers the least flexibility. It’s best for static graphs where the size is known beforehand and will not need to change.