Welcome to ✨ starbars’ ✨ documentation!

Welcome to ✨ starbars’ ✨ documentation!#

Contents:

This Python tool helps visualize statistical significance on existing Matplotlib plots by adding significance bars and p-value labels between chosen pairs of columns.

Features#

  • Converts p-values to asterisk notations for easy interpretation.

  • Draws statistical significance bars on Matplotlib plots.

  • Customizable bar margins, tip lengths, font sizes, and top margins.

  • Support bar plots, box plots, grouped bar plots (hue), and both horizontal and vertical data layout.

  • More features to ✨ come ✨.

Installation#

You can install the package via pip:

pip install starbars

Parameters#

  • annotations: List of tuples (x1, x2, p) containing the x-axis labels and the p-value of the pair.

  • ax: The axis of subplots to draw annotations on. If ax is not provided, it implies that you are working with a single plot rather than a set of subplots. In such cases, the annotations apply to the only existing plot in the figure.

  • ns_show: Whether to show bars for non-statistical pvalues. (Default: True)

  • bar_gap: Gap in between the bars of data. Default is 3% of the data axis.

  • tip_length: Length of the tip of the statistical bar. Default is 3% of the data axis.

  • top_margin: Margin of the last annotation from the top of the graph. Default is 5% of the data axis.

  • text_distance: Distance between the bar and the text. Default is 2% of the data axis.

  • fontsize: Font size of the annotations. Default is 10.

  • mode: orientation of the data representation, ‘horizontal’ or ‘vertical’. Default is ‘vertical’.

Example#

import starbars
import matplotlib.pyplot as plt

# Example data
categories = ['A', 'B', 'C']
values = [10, 20, 15]
annotations = [('A', 'B', 0.01), ('B', 'C', 0.05)]

plt.bar(categories, values)

# Annotate significance
starbars.draw_annotation(annotations)

plt.show()

(Source code, png, hires.png, pdf)

_images/index-1.png

Custom labels#

If you prefer different labels on the annotation bars, instead of passing your p-value, you may also pass any string you’d like. Starbars will then render it:

import starbars
import matplotlib.pyplot as plt

# Example data
categories = ['A', 'B', 'C']
values = [10, 20, 18]
annotations = [('A', 'B', 'p < 0.01'), ('B', 'C', 'not significant :(')]

plt.bar(categories, values)

# Annotate significance
starbars.draw_annotation(annotations)

plt.show()

(Source code, png, hires.png, pdf)

_images/index-2.png

License#

This project is licensed under the MIT License. See the LICENSE file for more details.

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