8000 Backport PR #15752 on branch v3.1.1-doc (Update boxplot/violinplot faq.) by meeseeksmachine · Pull Request #15761 · matplotlib/matplotlib · GitHub
[go: up one dir, main page]

Skip to content

Backport PR #15752 on branch v3.1.1-doc (Update boxplot/violinplot faq.) #15761

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
13 changes: 10 additions & 3 deletions doc/faq/howto_faq.rst
Original file line number Diff line number Diff line change
Expand Up @@ -557,12 +557,19 @@ though we have made significant progress towards supporting blocking events.
Interpreting box plots and violin plots
---------------------------------------

Tukey's `box plots <http://matplotlib.org/examples/pylab_examples/boxplot_demo.html>`_ (Robert McGill, John W. Tukey and Wayne A. Larsen: "The American Statistician" Vol. 32, No. 1, Feb., 1978, pp. 12-16) are statistical plots that provide useful information about the data distribution such as skewness. However, bar plots with error bars are still the common standard in most scientific literature, and thus, the interpretation of box plots can be challenging for the unfamiliar reader. The figure below illustrates the different visual features of a box plot.
Tukey's :doc:`box plots </gallery/statistics/boxplot_demo>` (Robert McGill,
John W. Tukey and Wayne A. Larsen: "The American Statistician" Vol. 32, No. 1,
Feb., 1978, pp. 12-16) are statistical plots that provide useful information
about the data distribution such as skewness. However, bar plots with error
bars are still the common standard in most scientific literature, and thus, the
interpretation of box plots can be challenging for the unfamiliar reader. The
figure below illustrates the different visual features of a box plot.

.. figure:: ../_static/boxplot_explanation.png

`Violin plots <http://matplotlib.org/examples/statistics/violinplot_demo.html>`_ are closely related to box plots but add useful information such as the distribution of the sample data (density trace).
Violin plots were added in Matplotlib 1.4.
:doc:`Violin plots </gallery/statistics/violinplot>` are closely related to box
plots but add useful information such as the distribution of the sample data
(density trace). Violin plots were added in Matplotlib 1.4.

.. _how-to-threads:

Expand Down
0