@@ -3801,7 +3801,7 @@ def boxplot(self, x, notch=None, sym=None, vert=None, whis=None,
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in *x*. If a sequence of 1D arrays, a boxplot is drawn for each
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array in *x*.
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- notch : bool, default: False
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+ notch : bool, default: :rc:`boxplot.notch`
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Whether to draw a notched boxplot (`True`), or a rectangular
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boxplot (`False`). The notches represent the confidence interval
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(CI) around the median. The documentation for *bootstrap*
@@ -3823,7 +3823,7 @@ def boxplot(self, x, notch=None, sym=None, vert=None, whis=None,
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the fliers. If `None`, then the fliers default to 'b+'. More
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control is provided by the *flierprops* parameter.
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- vert : bool, default: True
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+ vert : bool, default: :rc:`boxplot.vertical`
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If `True`, draws vertical boxes.
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If `False`, draw horizontal boxes.
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@@ -3880,7 +3880,7 @@ def boxplot(self, x, notch=None, sym=None, vert=None, whis=None,
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The widths of the boxes. The default is 0.5, or ``0.15*(distance
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between extreme positions)``, if that is smaller.
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- patch_artist : bool, default: False
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+ patch_artist : bool, default: :rc:`boxplot.patchartist`
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If `False` produces boxes with the Line2D artist. Otherwise,
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boxes are drawn with Patch artists.
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@@ -3896,7 +3896,7 @@ def boxplot(self, x, notch=None, sym=None, vert=None, whis=None,
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75th percentiles are equal, *whis* is set to (0, 100) such
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that the whisker ends are at the minimum and maximum of the data.
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- meanline : bool, default: False
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+ meanline : bool, default: :rc:`boxplot.meanline`
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If `True` (and *showmeans* is `True`), will try to render the
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mean as a line spanning the full width of the box according to
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*meanprops* (see below). Not recommended if *shownotches* is also
@@ -3931,13 +3931,13 @@ def boxplot(self, x, notch=None, sym=None, vert=None, whis=None,
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Other Parameters
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----------------
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- showcaps : bool, default: True
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+ showcaps : bool, default: :rc:`boxplot.showcaps`
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Show the caps on the ends of whiskers.
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- showbox : bool, default: True
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+ showbox : bool, default: :rc:`boxplot.showbox`
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Show the central box.
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- showfliers : bool, default: True
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+ showfliers : bool, default: :rc:`boxplot.showfliers`
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Show the outliers beyond the caps.
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- showmeans : bool, default: False
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+ showmeans : bool, default: :rc:`boxplot.showmeans`
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Show the arithmetic means.
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capprops : dict, default: None
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The style of the caps.
@@ -3958,6 +3958,7 @@ def boxplot(self, x, notch=None, sym=None, vert=None, whis=None,
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See Also
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--------
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+ .Axes.bxp : Draw a boxplot based on pre-computed statistics.
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violinplot : Draw an estimate of the probability density function.
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"""
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@@ -4086,13 +4087,26 @@ def bxp(self, bxpstats, positions=None, widths=None, vert=True,
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meanline = False , manage_ticks = True , zorder = None ,
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capwidths = None ):
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"""
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- Drawing function for box and whisker plots.
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+ Draw a box and whisker plot based on pre-computed statistics.
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+
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+ The box extends from the first quartile *q1* to the third
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+ quartile *q3* of the data, with a line at the median (*med*).
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+ The whiskers extend from *whislow* to *whishi*.
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+ Flier points are markers past the end of the whiskers.
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+ See https://en.wikipedia.org/wiki/Box_plot for reference.
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+
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+ .. code-block:: none
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+
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+ whislow q1 med q3 whishi
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+ |-----:-----|
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+ o |--------| : |--------| o o
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+ |-----:-----|
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+ flier fliers
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- Make a box and whisker plot for each column of *x* or each
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- vector in sequence *x*. The box extends from the lower to
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- upper quartile values of the data, with a line at the median.
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- The whiskers extend from the box to show the range of the
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- data. Flier points are those past the end of the whiskers.
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+ .. note::
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+ This is a low-level drawing function for when you already
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+ have the statistical parameters. If you want a boxplot based
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+ on a dataset, use `~.Axes.boxplot` instead.
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Parameters
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----------
@@ -4172,9 +4186,9 @@ def bxp(self, bxpstats, positions=None, widths=None, vert=True,
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- ``fliers``: points representing data beyond the whiskers (fliers).
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- ``means``: points or lines representing the means.
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- Examples
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+ See Also
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--------
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- .. plot:: gallery/statistics/bxp.py
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+ boxplot : Draw a boxplot based on data (instead of statistical parameters).
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"""
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# Clamp median line to edge of box by default.
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medianprops = {
@@ -8278,6 +8292,10 @@ def violinplot(self, dataset, positions=None, vert=True, widths=0.5,
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to identify the quantile values of each of the violin's
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distribution.
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+ See Also
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+ --------
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+ .Axes.violin : Draw a violin plot based on pre-computed statistics.
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+ boxplot : Draw a box and whisker plot.
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"""
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def _kde_method (X , coords ):
@@ -8298,7 +8316,7 @@ def _kde_method(X, coords):
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def violin (self , vpstats , positions = None , vert = True , widths = 0.5 ,
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showmeans = False , showextrema = True , showmedians = False ):
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"""
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- Drawing function for violin plots .
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+ Draw a violin plot based on pre-computed statistics .
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Draw a violin plot for each column of *vpstats*. Each filled area
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extends to represent the entire data range, with optional lines at the
@@ -8380,6 +8398,10 @@ def violin(self, vpstats, positions=None, vert=True, widths=0.5,
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- ``cquantiles``: A `~.collections.LineCollection` instance created
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to identify the quantiles values of each of the violin's
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distribution.
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+
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+ See Also
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+ --------
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+ violin : Draw a violin plot based on data (instead of statistical parameters).
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"""
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# Statistical quantities to be plotted on the violins
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