.create_bullet()

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dakshdeepHERE
Published Feb 25, 2025
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.create_bullet() is a function from the Plotly Figure Factory module that generates bullet charts. These charts compare a performance measure against predefined thresholds or ranges and are commonly used to visualize progress toward targets or key performance indicators (KPIs).

Syntax

plotly.figure_factory.create_bullet(
  data,
  markers=None,
  measures=None,
  ranges=None,
  subtitles=None,
  titles=None,
  orientation='h',
  width=None,
  height=None,
  **layout_options
)
Parameter Description
data A list of dictionaries or a similar data structure describing chart parameters for each bullet.
markers A list of target or reference values (for example, the goal).
measures A list of actual values representing the performance metric being tracked.
ranges A list of numeric intervals that define color-coded zones for context.
subtitles A list of text labels for additional information or descriptions.
titles A list of main titles or labels for each bullet.
orientation Determines chart direction: 'h' (horizontal, default) or 'v' (vertical).
width, height The figure’s width and height in pixels.
**layout_options Additional layout attributes passed to the underlying Plotly figure (for example, margins, background color).

Returns: A Plotly figure object that can be displayed or updated using standard Plotly methods.

Example

The example below demonstrates the usage of .create_bullet() function:

import plotly.figure_factory as ff


bullet_data = [
  {
    'title': 'Sales',
    'subtitle': 'in thousands',
    'ranges': [20, 30, 40],
    'measures': [22],
    'markers': [30]
  }
]


fig = ff.create_bullet(
  data=bullet_data,
  orientation='h',
  width=600,
  height=200
)


fig.update_layout(
  title="Bullet Chart Example"
)


fig.show()
  • bullet_data defines the ranges, measures, and markers for the bullet chart.
  • create_bullet() builds the chart with a chosen orientation and size.
  • update_layout() modifies the layout, including adding a title.
  • fig.show() displays the chart in an interactive environment such as Jupyter Notebook.

Here’s how the output will look like:

The output for the above example

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