Repository: matplotlib/matplotlib
File: lib/matplotlib/axes/_axes.py (Python)

Code before:
                        x_masked, y_masked, marker=marker, **eb_cap_style))
        if self.name == 'polar':
            trans_shift = self.transShift
            for axis in caplines:
                for l in caplines[axis]:
                    # Rotate caps to be perpendicular to the error bars
                    for theta, r in zip(l.get_xdata(), l.get_ydata()):
                        rotation = _ScaledRotation(theta=theta, trans_shift=trans_shift)
                        if axis == 'y':
                            rotation += mtransforms.Affine2D().rotate(np.pi / 2)
                        ms = mmarkers.MarkerStyle(marker=marker,
                                                  transform=rotation)
                        self.add_line(mlines.Line2D([theta], [r], marker=ms,
                                                    **eb_cap_style))
        else:
            for axis in caplines:
                for l in caplines[axis]:
                    self.add_line(l)

        self._request_autoscale_view()
        caplines = caplines['x'] + caplines['y']

        if(elinestyle is not None):
            if(xerr is not None and yerr is not None): 
                barcols[-2].set_linestyle(elinestyle)
                barcols[-1].set_linestyle(elinestyle)


        errorbar_container = ErrorbarContainer(
            (data_line, tuple(caplines), tuple(barcols)),
            has_xerr=(xerr is not None), has_yerr=(yerr is not None),
            label=label)
        self.add_container(errorbar_container)

        return errorbar_container  # (l0, caplines, barcols)

    @_api.make_keyword_only("3.10", "notch")
    @_preprocess_data()
    @_api.rename_parameter("3.9", "labels", "tick_labels")
    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):
        """
        Draw a box and whisker plot.

Review comment (suggestion):
Instead of modifying this here afterwards, please set the style in `eb_lines_style` (around line 3700).

Code after:
                    else lomarker)
                x_masked, y_masked, hl_masked = apply_mask(
                    [x, y, hl], lims & everymask)
                # As above, we set the dependent data in a second step.
                line = mlines.Line2D(x_masked, y_masked,
                                     marker=hlmarker, **eb_cap_style)
                line.set(**{f"{dep_axis}data": hl_masked})
                caplines[dep_axis].append(line)
                if capsize > 0:
                    caplines[dep_axis].append(mlines.Line2D(
                        x_masked, y_masked, marker=marker, **eb_cap_style))
        if self.name == 'polar':
            trans_shift = self.transShift
            for axis in caplines:
                for l in caplines[axis]:
                    # Rotate caps to be perpendicular to the error bars
                    for theta, r in zip(l.get_xdata(), l.get_ydata()):
                        rotation = _ScaledRotation(theta=theta, trans_shift=trans_shift)
                        if axis == 'y':
                            rotation += mtransforms.Affine2D().rotate(np.pi / 2)
                        ms = mmarkers.MarkerStyle(marker=marker,
                                                  transform=rotation)
                        self.add_line(mlines.Line2D([theta], [r], marker=ms,
                                                    **eb_cap_style))
        else:
            for axis in caplines:
                for l in caplines[axis]:
                    self.add_line(l)

        self._request_autoscale_view()
        caplines = caplines['x'] + caplines['y']
        errorbar_container = ErrorbarContainer(
            (data_line, tuple(caplines), tuple(barcols)),
            has_xerr=(xerr is not None), has_yerr=(yerr is not None),
            label=label)
        self.add_container(errorbar_container)

        return errorbar_container  # (l0, caplines, barcols)

    @_api.make_keyword_only("3.10", "notch")
    @_preprocess_data()
    @_api.rename_parameter("3.9", "labels", "tick_labels")
    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,