UpSetPlot 0.4.0

Draw Lex et al.'s UpSet plots with Pandas and Matplotlib

UpSetPlot documentation
============================

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This is another Python implementation of UpSet plots by Lex et al. [Lex2014]_.
UpSet plots are used to visualise set overlaps; like Venn diagrams but
more readable. Documentation is at https://upsetplot.readthedocs.io.

This ``upsetplot`` library tries to provide a simple interface backed by an
extensible, object-oriented design.

The basic input format is a `pandas.Series` containing counts corresponding to
subset sizes, where each subset is an intersection of named categories. The
index of the Series indicates which rows pertain to which categories, by having
multiple boolean indices, like ``example`` in the following::

>>> from upsetplot import generate_counts
>>> example = generate_counts()
>>> example # doctest: +NORMALIZE_WHITESPACE
cat0 cat1 cat2
False False False 56
True 283
True False 1279
True 5882
True False False 24
True 90
True False 429
True 1957
Name: value, dtype: int64

Then::

>>> from upsetplot import plot
>>> plot(example) # doctest: +SKIP
>>> from matplotlib import pyplot
>>> pyplot.show() # doctest: +SKIP

makes:

.. image:: http://upsetplot.readthedocs.io/en/latest/_images/sphx_glr_plot_generated_001.png
:target: ../auto_examples/plot_generated.html

This plot shows the cardinality of every category combination seen in our data.
The leftmost column counts items absent from any category. The next three
columns count items only in ``cat1``, ``cat2`` and ``cat3`` respectively, with
following columns showing cardinalities for items in each combination of
exactly two named sets. The rightmost column counts items in all three sets.

Rotation
........

We call the above plot style "horizontal" because the category intersections
are presented from left to right. `Vertical plots
<http://upsetplot.readthedocs.io/en/latest/auto_examples/plot_vertical.html>`__
are also supported!

.. image:: http://upsetplot.readthedocs.io/en/latest/_images/sphx_glr_plot_vertical_001.png
:target: http://upsetplot.readthedocs.io/en/latest/auto_examples/plot_vertical.html

Distributions
.............

Providing a DataFrame rather than a Series as input allows us to expressively
`plot the distribution of variables
<http://upsetplot.readthedocs.io/en/latest/auto_examples/plot_boston.html>`__
in each subset.

.. image:: http://upsetplot.readthedocs.io/en/latest/_images/sphx_glr_plot_boston_001.png
:target: http://upsetplot.readthedocs.io/en/latest/auto_examples/plot_boston.html

Loading datasets
................

While the dataset above is randomly generated, you can prepare your own dataset
for input to upsetplot. A helpful tool is `from_memberships`, which allows
us to reconstruct the example above by indicating each data point's category
membership::

>>> from upsetplot import from_memberships
>>> example = from_memberships(
... [[],
... ['cat2'],
... ['cat1'],
... ['cat1', 'cat2'],
... ['cat0'],
... ['cat0', 'cat2'],
... ['cat0', 'cat1'],
... ['cat0', 'cat1', 'cat2'],
... ],
... data=[56, 283, 1279, 5882, 24, 90, 429, 1957]
... )
>>> example # doctest: +NORMALIZE_WHITESPACE
cat0 cat1 cat2
False False False 56
True 283
True False 1279
True 5882
True False False 24
True 90
True False 429
True 1957
dtype: int64

See also `from_contents`, another way to describe categorised data.

Installation
------------

To install the library, you can use `pip`::

$ pip install upsetplot

Installation requires:

* pandas
* matplotlib >= 2.0
* seaborn to use `UpSet.add_catplot`

It should then be possible to::

>>> import upsetplot

in Python.

Why an alternative to py-upset?
-------------------------------

Probably for petty reasons. It appeared `py-upset
<https://github.com/ImSoErgodic/py-upset>`_ was not being maintained. Its
input format was undocumented, inefficient and, IMO, inappropriate. It did not
facilitate showing plots of each subset's distribution as in Lex et al's work
introducing UpSet plots. Nor did it include the horizontal bar plots
illustrated there. It did not support Python 2. I decided it would be easier to
construct a cleaner version than to fix it.

References
----------

.. [Lex2014] Alexander Lex, Nils Gehlenborg, Hendrik Strobelt, Romain Vuillemot, Hanspeter Pfister,
*UpSet: Visualization of Intersecting Sets*,
IEEE Transactions on Visualization and Computer Graphics (InfoVis '14), vol. 20, no. 12, pp. 1983–1992, 2014.
doi: `doi.org/10.1109/TVCG.2014.2346248 <https://doi.org/10.1109/TVCG.2014.2346248>`_


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