----:-----| 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: False 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, default: True If `True`, draws vertical boxes. If `False`, draw horizontal boxes. 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: False If `False` produces boxes with the Line2D artist. Otherwise, boxes are drawn with Patch artists. labels : sequence, optional Labels for each dataset (one per dataset). 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: False 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: True Show the caps on the ends of whiskers. showbox : bool, default: True Show the central box. showfliers : bool, default: True Show the outliers beyond the caps. showmeans : bool, default: False 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. data : indexable object, optional DATA_PARAMETER_PLACEHOLDER See Also -------- violinplot : Draw an estimate of the probability density function. Nz