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def boxplot(self, x, *, notch=None, sym=None, vert=None, orientation='vertical', whis=None, positions=None, widths=None, patch_artist=None, bootstrap=None, usermedians=None, conf_intervals=None, meanline=None, showmeans=None, showcaps=None, showbox=None, showfliers=None, boxprops=None, tick_labels=None, flierprops=None, medianprops=None, meanprops=None, capprops=None, whiskerprops=None, manage_ticks=True, autorange=False, zorder=None, capwidths=None, label=None, data=None)
Draw a box and whisker plot.
The box extends from the first quartile (Q1) to the third
quartile (Q3) of the data, with a line at the median.
The whiskers extend from the box to the farthest data point
lying within 1.5x the inter-quartile range (IQR) from the box.
Flier points are those past the end of the whiskers.
See https://en.wikipedia.org/wiki/Box_plot for reference.
.. code-block:: none
Q1-1.5IQR Q1 median Q3 Q3+1.5IQR
|-----:-----|
o |--------| : |--------| o o
|-----:-----|
flier <-----------> fliers
IQR
Parameters
----------
x : Array or a sequence of vectors.
The input data. If a 2D array, a boxplot is drawn for each column
in *x*. If a sequence of 1D arrays, a boxplot is drawn for each
array in *x*.
notch : bool, default: :rc:`boxplot.notch`
Whether to draw a notched boxplot (`True`), or a rectangular
boxplot (`False`). The notches represent the confidence interval
(CI) around the median. The documentation for *bootstrap*
describes how the locations of the notches are computed by
default, but their locations may also be overridden by setting the
*conf_intervals* parameter.
.. note::
In cases where the values of the CI are less than the
lower quartile or greater than the upper quartile, the
notches will extend beyond the box, giving it a
distinctive "flipped" appearance. This is expected
behavior and consistent with other statistical
visualization packages.
sym : str, optional
The default symbol for flier points. An empty string ('') hides
the fliers. If `None`, then the fliers default to 'b+'. More
control is provided by the *flierprops* parameter.
vert : bool, optional
.. deprecated:: 3.11
Use *orientation* instead.
This is a pending deprecation for 3.10, with full deprecation
in 3.11 and removal in 3.13.
If this is given during the deprecation period, it overrides
the *orientation* parameter.
If True, plots the boxes vertically.
If False, plots the boxes horizontally.
orientation : {'vertical', 'horizontal'}, default: 'vertical'
If 'horizontal', plots the boxes horizontally.
Otherwise, plots the boxes vertically.
.. versionadded:: 3.10
whis : float or (float, float), default: 1.5
The position of the whiskers.
If a float, the lower whisker is at the lowest datum above
``Q1 - whis*(Q3-Q1)``, and the upper whisker at the highest datum
below ``Q3 + whis*(Q3-Q1)``, where Q1 and Q3 are the first and
third quartiles. The default value of ``whis = 1.5`` corresponds
to Tukey's original definition of boxplots.
If a pair of floats, they indicate the percentiles at which to
draw the whiskers (e.g., (5, 95)). In particular, setting this to
(0, 100) results in whiskers covering the whole range of the data.
In the edge case where ``Q1 == Q3``, *whis* is automatically set
to (0, 100) (cover the whole range of the data) if *autorange* is
True.
Beyond the whiskers, data are considered outliers and are plotted
as individual points.
bootstrap : int, optional
Specifies whether to bootstrap the confidence intervals
around the median for notched boxplots. If *bootstrap* is
None, no bootstrapping is performed, and notches are
calculated using a Gaussian-based asymptotic approximation
(see McGill, R., Tukey, J.W., and Larsen, W.A., 1978, and
Kendall and Stuart, 1967). Otherwise, bootstrap specifies
the number of times to bootstrap the median to determine its
95% confidence intervals. Values between 1000 and 10000 are
recommended.
usermedians : 1D array-like, optional
A 1D array-like of length ``len(x)``. Each entry that is not
`None` forces the value of the median for the corresponding
dataset. For entries that are `None`, the medians are computed
by Matplotlib as normal.
conf_intervals : array-like, optional
A 2D array-like of shape ``(len(x), 2)``. Each entry that is not
None forces the location of the corresponding notch (which is
only drawn if *notch* is `True`). For entries that are `None`,
the notches are computed by the method specified by the other
parameters (e.g., *bootstrap*).
positions : array-like, optional
The positions of the boxes. The ticks and limits are
automatically set to match the positions. Defaults to
``range(1, N+1)`` where N is the number of boxes to be drawn.
widths : float or array-like
The widths of the boxes. The default is 0.5, or ``0.15*(distance
between extreme positions)``, if that is smaller.
patch_artist : bool, default: :rc:`boxplot.patchartist`
If `False` produces boxes with the Line2D artist. Otherwise,
boxes are drawn with Patch artists.
tick_labels : list of str, optional
The tick labels of each boxplot.
Ticks are always placed at the box *positions*. If *tick_labels* is given,
the ticks are labelled accordingly. Otherwise, they keep their numeric
values.
.. versionchanged:: 3.9
Renamed from *labels*, which is deprecated since 3.9
and will be removed in 3.11.
manage_ticks : bool, default: True
If True, the tick locations and labels will be adjusted to match
the boxplot positions.
autorange : bool, default: False
When `True` and the data are distributed such that the 25th and
75th percentiles are equal, *whis* is set to (0, 100) such
that the whisker ends are at the minimum and maximum of the data.
meanline : bool, default: :rc:`boxplot.meanline`
If `True` (and *showmeans* is `True`), will try to render the
mean as a line spanning the full width of the box according to
*meanprops* (see below). Not recommended if *shownotches* is also
True. Otherwise, means will be shown as points.
zorder : float, default: ``Line2D.zorder = 2``
The zorder of the boxplot.
Returns
-------
dict
A dictionary mapping each component of the boxplot to a list
of the `.Line2D` instances created. That dictionary has the
following keys (assuming vertical boxplots):
- ``boxes``: the main body of the boxplot showing the
quartiles and the median's confidence intervals if
enabled.
- ``medians``: horizontal lines at the median of each box.
- ``whiskers``: the vertical lines extending to the most
extreme, non-outlier data points.
- ``caps``: the horizontal lines at the ends of the
whiskers.
- ``fliers``: points representing data that extend beyond
the whiskers (fliers).
- ``means``: points or lines representing the means.
Other Parameters
----------------
showcaps : bool, default: :rc:`boxplot.showcaps`
Show the caps on the ends of whiskers.
showbox : bool, default: :rc:`boxplot.showbox`
Show the central box.
showfliers : bool, default: :rc:`boxplot.showfliers`
Show the outliers beyond the caps.
showmeans : bool, default: :rc:`boxplot.showmeans`
Show the arithmetic means.
capprops : dict, default: None
The style of the caps.
capwidths : float or array, default: None
The widths of the caps.
boxprops : dict, default: None
The style of the box.
whiskerprops : dict, default: None
The style of the whiskers.
flierprops : dict, default: None
The style of the fliers.
medianprops : dict, default: None
The style of the median.
meanprops : dict, default: None
The style of the mean.
label : str or list of str, optional
Legend labels. Use a single string when all boxes have the same style and
you only want a single legend entry for them. Use a list of strings to
label all boxes individually. To be distinguishable, the boxes should be
styled individually, which is currently only possible by modifying the
returned artists, see e.g. :doc:`/gallery/statistics/boxplot_demo`.
In the case of a single string, the legend entry will technically be
associated with the first box only. By default, the legend will show the
median line (``result["medians"]``); if *patch_artist* is True, the legend
will show the box `.Patch` artists (``result["boxes"]``) instead.
.. versionadded:: 3.9
data : indexable object, optional
If given, all parameters also accept a string ``s``, which is
interpreted as ``data[s]`` if ``s`` is a key in ``data``.
See Also
--------
.Axes.bxp : Draw a boxplot from pre-computed statistics.
violinplot : Draw an estimate of the probability density function.
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