10000 DOC: Update violinplot() docs · matplotlib/matplotlib@1d3769c · GitHub
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DOC: Update violinplot() docs
Some corrections and small rewrites.
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‎lib/matplotlib/axes/_axes.py

Lines changed: 23 additions & 24 deletions
Original file line numberDiff line numberDiff line change
@@ -8206,43 +8206,42 @@ def violinplot(self, dataset, positions=None, vert=True, widths=0.5,
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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. The ticks and limits are
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automatically set to match the positions.
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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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widths : array-like, default: 0.5
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Either a scalar or a vector that sets the maximal width of
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each violin. The default is 0.5, which uses about half of the
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available horizontal space.
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widths : float or array-like, default: 0.5
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The maximal 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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If `True`, will toggle rendering of the means.
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Whether to indicate the mean with a line.
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showextrema : bool, default: True
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If `True`, will toggle rendering of the extrema.
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Whether to indicate the extrema with a line.
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showmedians : bool, default: False
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If `True`, will toggle rendering of the medians.
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Whether to indicate 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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points : int, default: 100
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Defines the number of points to evaluate each of the
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gaussian kernel density 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 : str, scalar or callable, optional
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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. This can be
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'scott', 'silverman', a scalar constant or a callable. If a
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scalar, this will be used directly as `kde.factor`. 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 scalar. If None (default), 'scott'
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is used.
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its only parameter and return a float.
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data : indexable object, optional
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DATA_PARAMETER_PLACEHOLDER
@@ -8329,26 +8328,26 @@ def violin(self, vpstats, positions=None, vert=True, widths=0.5,
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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. The ticks and limits are
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automatically set to match the positions.
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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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widths : array-like, default: 0.5
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Either a scalar or a vector that sets the maximal width of
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each violin. The default is 0.5, which uses about half of the
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available horizontal space.
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widths : float or array-like, default: 0.5
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The maximal 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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If true, will toggle rendering of the means.
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Whether to indicate the mean with a line.
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showextrema : bool, default: True
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If true, will toggle rendering of the extrema.
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Whether to indicate the extrema with a line.
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showmedians : bool, default: False
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If true, will toggle rendering of the medians.
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Whether to indicate the median with a line.
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Returns
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-------

‎lib/matplotlib/mlab.py

Lines changed: 3 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -776,12 +776,12 @@ class GaussianKDE:
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dataset : array-like
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Datapoints to estimate from. In case of univariate data this is a 1-D
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array, otherwise a 2D array with shape (# of dims, # of data).
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bw_method : str, scalar or callable, optional
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bw_method : {'scott', 'silverman'} or float or callable, optional
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The method used to calculate the estimator bandwidth. This can be
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'scott', 'silverman', a scalar constant or a callable. If a
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scalar, this will be used directly as `kde.factor`. 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 `GaussianKDE` instance as only
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parameter and return a scalar. If None (default), 'scott' is used.
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parameter and return a float. If None (default), 'scott' is used.
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Attributes
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----------

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