@@ -4176,62 +4176,62 @@ def bxp(self, bxpstats, positions=None, widths=None, vert=True,
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Parameters
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----------
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bxpstats : list of dicts
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- A list of dictionaries containing stats for each boxplot.
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- Required keys are:
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+ A list of dictionaries containing stats for each boxplot.
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+ Required keys are:
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- - ``med``: Median (scalar).
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- - ``q1``, ``q3``: First & third quartiles (scalars).
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- - ``whislo``, ``whishi``: Lower & upper whisker positions (scalars).
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+ - ``med``: Median (scalar).
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+ - ``q1``, ``q3``: First & third quartiles (scalars).
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+ - ``whislo``, ``whishi``: Lower & upper whisker positions (scalars).
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- Optional keys are:
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+ Optional keys are:
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- - ``mean``: Mean (scalar). Needed if ``showmeans=True``.
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- - ``fliers``: Data beyond the whiskers (array-like).
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- Needed if ``showfliers=True``.
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- - ``cilo``, ``cihi``: Lower & upper confidence intervals
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- about the median. Needed if ``shownotches=True``.
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- - ``label``: Name of the dataset (str). If available,
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- this will be used a tick label for the boxplot
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+ - ``mean``: Mean (scalar). Needed if ``showmeans=True``.
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+ - ``fliers``: Data beyond the whiskers (array-like).
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+ Needed if ``showfliers=True``.
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+ - ``cilo``, ``cihi``: Lower & upper confidence intervals
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+ about the median. Needed if ``shownotches=True``.
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+ - ``label``: Name of the dataset (str). If available,
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+ this will be used a tick label for the boxplot
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positions : array-like, default: [1, 2, ..., n]
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- The positions of the boxes. The ticks and limits
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- are automatically set to match the positions.
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+ The positions of the boxes. The ticks and limits
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+ are automatically set to match the positions.
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widths : float or array-like, default: None
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- The widths of the boxes. The default is
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- ``clip(0.15*(distance between extreme positions), 0.15, 0.5)``.
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+ The widths of the boxes. The default is
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+ ``clip(0.15*(distance between extreme positions), 0.15, 0.5)``.
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capwidths : float or array-like, default: None
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- Either a scalar or a vector and sets the width of each cap.
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- The default is ``0.5*(width of the box)``, see *widths*.
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+ Either a scalar or a vector and sets the width of each cap.
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+ The default is ``0.5*(width of the box)``, see *widths*.
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vert : bool, default: True
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- If `True` (default), makes the boxes vertical.
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- If `False`, makes horizontal boxes.
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+ If `True` (default), makes the boxes vertical.
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+ If `False`, makes horizontal boxes.
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patch_artist : bool, default: False
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- If `False` produces boxes with the `.Line2D` artist.
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- If `True` produces boxes with the `~matplotlib.patches.Patch` artist.
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+ If `False` produces boxes with the `.Line2D` artist.
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+ If `True` produces boxes with the `~matplotlib.patches.Patch` artist.
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shownotches, showmeans, showcaps, showbox, showfliers : bool
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- Whether to draw the CI notches, the mean value (both default to
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- False), the caps, the box, and the fliers (all three default to
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- True).
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+ Whether to draw the CI notches, the mean value (both default to
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+ False), the caps, the box, and the fliers (all three default to
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+ True).
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boxprops, whiskerprops, capprops, flierprops, medianprops, meanprops :\
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dict, optional
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- Artist properties for the boxes, whiskers, caps, fliers, medians, and
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- means.
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+ Artist properties for the boxes, whiskers, caps, fliers, medians, and
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+ means.
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meanline : bool, default: False
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- If `True` (and *showmeans* is `True`), will try to render the mean
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- as a line spanning the full width of the box according to
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- *meanprops*. Not recommended if *shownotches* is also True.
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- Otherwise, means will be shown as points.
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+ If `True` (and *showmeans* is `True`), will try to render the mean
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+ as a line spanning the full width of the box according to
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+ *meanprops*. Not recommended if *shownotches* is also True.
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+ Otherwise, means will be shown as points.
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manage_ticks : bool, default: True
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- If True, the tick locations and labels will be adjusted to match the
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- boxplot positions.
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+ If True, the tick locations and labels will be adjusted to match the
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+ boxplot positions.
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label : str or list of str, optional
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Legend labels. Use a single string when all boxes have the same style and
@@ -4248,22 +4248,22 @@ def bxp(self, bxpstats, positions=None, widths=None, vert=True,
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.. versionadded:: 3.9
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zorder : float, default: ``Line2D.zorder = 2``
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- The zorder of the resulting boxplot.
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+ The zorder of the resulting boxplot.
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Returns
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-------
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dict
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- A dictionary mapping each component of the boxplot to a list
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- of the `.Line2D` instances created. That dictionary has the
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- following keys (assuming vertical boxplots):
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-
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- - ``boxes``: main bodies of the boxplot showing the quartiles, and
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- the median's confidence intervals if enabled.
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- - ``medians``: horizontal lines at the median of each box.
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- - ``whiskers``: vertical lines up to the last non-outlier data.
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- - ``caps``: horizontal lines at the ends of the whiskers.
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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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+ A dictionary mapping each component of the boxplot to a list
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+ of the `.Line2D` instances created. That dictionary has the
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+ following keys (assuming vertical boxplots):
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+
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+ - ``boxes``: main bodies of the boxplot showing the quartiles, and
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+ the median's confidence intervals if enabled.
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+ - ``medians``: horizontal lines at the median of each box.
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+ - ``whiskers``: vertical lines up to the last non-outlier data.
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+ - ``caps``: horizontal lines at the ends of the whiskers.
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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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See Also
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--------
@@ -6468,7 +6468,7 @@ def pcolorfast(self, *args, alpha=None, norm=None, cmap=None, vmin=None,
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Call signature::
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- ax.pcolorfast([X, Y], C, /, **kwargs)
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+ ax.pcolorfast([X, Y], C, /, **kwargs)
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This method is similar to `~.Axes.pcolor` and `~.Axes.pcolormesh`.
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It's designed to provide the fastest pcolor-type plotting with the
@@ -6478,12 +6478,12 @@ def pcolorfast(self, *args, alpha=None, norm=None, cmap=None, vmin=None,
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.. warning::
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- This method is experimental. Compared to `~.Axes.pcolor` or
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- `~.Axes.pcolormesh` it has some limitations:
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+ This method is experimental. Compared to `~.Axes.pcolor` or
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+ `~.Axes.pcolormesh` it has some limitations:
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- - It supports only flat shading (no outlines)
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- - It lacks support for log scaling of the axes.
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- - It does not have a pyplot wrapper.
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+ - It supports only flat shading (no outlines)
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+ - It lacks support for log scaling of the axes.
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+ - It does not have a pyplot wrapper.
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Parameters
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----------
@@ -8316,44 +8316,44 @@ def violinplot(self, dataset, positions=None, vert=True, widths=0.5,
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Parameters
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----------
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dataset : Array or a sequence of vectors.
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- The input data.
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+ The input data.
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positions : array-like, default: [1, 2, ..., n]
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- The positions of the violins; i.e. coordinates on the x-axis for
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- vertical violins (or y-axis for horizontal violins).
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+ The positions of the violins; i.e. coordinates on the x-axis for
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+ vertical violins (or y-axis for horizontal violins).
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vert : bool, default: True.
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- If true, creates a vertical violin plot.
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- Otherwise, creates a horizontal violin plot.
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+ If true, creates a vertical violin plot.
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+ Otherwise, creates a horizontal violin plot.
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widths : float or array-like, default: 0.5
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- The maximum width of each violin in units of the *positions* axis.
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- The default is 0.5, which is half the available space when using default
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- *positions*.
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+ The maximum width of each violin in units of the *positions* axis.
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+ The default is 0.5, which is half the available space when using default
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+ *positions*.
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showmeans : bool, default: False
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- Whether to show the mean with a line.
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+ Whether to show the mean with a line.
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showextrema : bool, default: True
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- Whether to show extrema with a line.
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+ Whether to show extrema with a line.
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showmedians : bool, default: False
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- Whether to show the median with a line.
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+ Whether to show the median with a line.
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quantiles : array-like, default: None
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- If not None, set a list of floats in interval [0, 1] for each violin,
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- which stands for the quantiles that will be rendered for that
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- violin.
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+ If not None, set a list of floats in interval [0, 1] for each violin,
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+ which stands for the quantiles that will be rendered for that
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+ violin.
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points : int, default: 100
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- The number of points to evaluate each of the gaussian kernel density
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- estimations at.
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+ The number of points to evaluate each of the gaussian kernel density
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+ estimations at.
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bw_method : {'scott', 'silverman'} or float or callable, default: 'scott'
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- The method used to calculate the estimator bandwidth. If a
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- float, this will be used directly as `kde.factor`. If a
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- callable, it should take a `matplotlib.mlab.GaussianKDE` instance as
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- its only parameter and return a float.
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+ The method used to calculate the estimator bandwidth. If a
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+ float, this will be used directly as `kde.factor`. If a
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+ callable, it should take a `matplotlib.mlab.GaussianKDE` instance as
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+ its only parameter and return a float.
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side : {'both', 'low', 'high'}, default: 'both'
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'both' plots standard violins. 'low'/'high' only
@@ -8365,31 +8365,31 @@ def violinplot(self, dataset, positions=None, vert=True, widths=0.5,
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Returns
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-------
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dict
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- A dictionary mapping each component of the violinplot to a
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- list of the corresponding collection instances created. The
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- dictionary has the following keys:
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+ A dictionary mapping each component of the violinplot to a
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+ list of the corresponding collection instances created. The
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+ dictionary has the following keys:
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- - ``bodies``: A list of the `~.collections.PolyCollection`
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- instances containing the filled area of each violin.
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+ - ``bodies``: A list of the `~.collections.PolyCollection`
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+ instances containing the filled area of each violin.
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- - ``cmeans``: A `~.collections.LineCollection` instance that marks
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- the mean values of each of the violin's distribution.
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+ - ``cmeans``: A `~.collections.LineCollection` instance that marks
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+ the mean values of each of the violin's distribution.
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- - ``cmins``: A `~.collections.LineCollection` instance that marks
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- the bottom of each violin's distribution.
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+ - ``cmins``: A `~.collections.LineCollection` instance that marks
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+ the bottom of each violin's distribution.
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- - ``cmaxes``: A `~.collections.LineCollection` instance that marks
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- the top of each violin's distribution.
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+ - ``cmaxes``: A `~.collections.LineCollection` instance that marks
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+ the top of each violin's distribution.
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- - ``cbars``: A `~.collections.LineCollection` instance that marks
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- the centers of each violin's distribution.
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+ - ``cbars``: A `~.collections.LineCollection` instance that marks
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+ the centers of each violin's distribution.
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- - ``cmedians``: A `~.collections.LineCollection` instance that
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- marks the median values of each of the violin's distribution.
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+ - ``cmedians``: A `~.collections.LineCollection` instance that
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+ marks the median values of each of the violin's distribution.
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- - ``cquantiles``: A `~.collections.LineCollection` instance created
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- to identify the quantile values of each of the violin's
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- distribution.
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+ - ``cquantiles``: A `~.collections.LineCollection` instance created
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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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--------
@@ -8424,50 +8424,50 @@ def violin(self, vpstats, positions=None, vert=True, widths=0.5,
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Parameters
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----------
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vpstats : list of dicts
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- A list of dictionaries containing stats for each violin plot.
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- Required keys are:
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+ A list of dictionaries containing stats for each violin plot.
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+ Required keys are:
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- - ``coords``: A list of scalars containing the coordinates that
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- the violin's kernel density estimate were evaluated at.
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+ - ``coords``: A list of scalars containing the coordinates that
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+ the violin's kernel density estimate were evaluated at.
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- - ``vals``: A list of scalars containing the values of the
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- kernel density estimate at each of the coordinates given
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- in *coords*.
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+ - ``vals``: A list of scalars containing the values of the
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+ kernel density estimate at each of the coordinates given
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+ in *coords*.
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- - ``mean``: The mean value for this violin's dataset.
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+ - ``mean``: The mean value for this violin's dataset.
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- - ``median``: The median value for this violin's dataset.
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+ - ``median``: The median value for this violin's dataset.
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- - ``min``: The minimum value for this violin's dataset.
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+ - ``min``: The minimum value for this violin's dataset.
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- - ``max``: The maximum value for this violin's dataset.
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+ - ``max``: The maximum value for this violin's dataset.
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- Optional keys are:
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+ Optional keys are:
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- - ``quantiles``: A list of scalars containing the quantile values
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- for this violin's dataset.
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+ - ``quantiles``: A list of scalars containing the quantile values
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+ for this violin's dataset.
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positions : array-like, default: [1, 2, ..., n]
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- The positions of the violins; i.e. coordinates on the x-axis for
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- vertical violins (or y-axis for horizontal violins).
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+ The positions of the violins; i.e. coordinates on the x-axis for
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+ vertical violins (or y-axis for horizontal violins).
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vert : bool, default: True.
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- If true, plots the violins vertically.
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- Otherwise, plots the violins horizontally.
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+ If true, plots the violins vertically.
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+ Otherwise, plots the violins horizontally.
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widths : float or array-like, default: 0.5
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- The maximum width of each violin in units of the *positions* axis.
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- The default is 0.5, which is half available space when using default
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- *positions*.
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+ The maximum width of each violin in units of the *positions* axis.
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+ The default is 0.5, which is half available space when using default
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+ *positions*.
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showmeans : bool, default: False
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- Whether to show the mean with a line.
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+ Whether to show the mean with a line.
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showextrema : bool, default: True
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- Whether to show extrema with a line.
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+ Whether to show extrema with a line.
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showmedians : bool, default: False
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- Whether to show the median with a line.
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+ Whether to show the median with a line.
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side : {'both', 'low', 'high'}, default: 'both'
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'both' plots standard violins. 'low'/'high' only
@@ -8476,31 +8476,31 @@ def violin(self, vpstats, positions=None, vert=True, widths=0.5,
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Returns
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-------
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dict
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- A dictionary mapping each component of the violinplot to a
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- list of the corresponding collection instances created. The
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- dictionary has the following keys:
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+ A dictionary mapping each component of the violinplot to a
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+ list of the corresponding collection instances created. The
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+ dictionary has the following keys:
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- - ``bodies``: A list of the `~.collections.PolyCollection`
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- instances containing the filled area of each violin.
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+ - ``bodies``: A list of the `~.collections.PolyCollection`
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+ instances containing the filled area of each violin.
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- - ``cmeans``: A `~.collections.LineCollection` instance that marks
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- the mean values of each of the violin's distribution.
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+ - ``cmeans``: A `~.collections.LineCollection` instance that marks
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+ the mean values of each of the violin's distribution.
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- - ``cmins``: A `~.collections.LineCollection` instance that marks
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- the bottom of each violin's distribution.
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+ - ``cmins``: A `~.collections.LineCollection` instance that marks
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+ the bottom of each violin's distribution.
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- - ``cmaxes``: A `~.collections.LineCollection` instance that marks
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- the top of each violin's distribution.
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+ - ``cmaxes``: A `~.collections.LineCollection` instance that marks
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+ the top of each violin's distribution.
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- - ``cbars``: A `~.collections.LineCollection` instance that marks
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- the centers of each violin's distribution.
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+ - ``cbars``: A `~.collections.LineCollection` instance that marks
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+ the centers of each violin's distribution.
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- - ``cmedians``: A `~.collections.LineCollection` instance that
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- marks the median values of each of the violin's distribution.
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+ - ``cmedians``: A `~.collections.LineCollection` instance that
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+ marks the median values of each of the violin's distribution.
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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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+ - ``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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See Also
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--------
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