def test_grouped_hist_legacy(self):
        from matplotlib.patches import Rectangle

        df = DataFrame(randn(500, 2), columns=['A', 'B'])
        df['C'] = np.random.randint(0, 4, 500)
        df['D'] = ['X'] * 500

        axes = grouped_hist(df.A, by=df.C)
        self._check_axes_shape(axes, axes_num=4, layout=(2, 2))

        tm.close()
        axes = df.hist(by=df.C)
        self._check_axes_shape(axes, axes_num=4, layout=(2, 2))

        tm.close()
        # group by a key with single value
        axes = df.hist(by='D', rot=30)
        self._check_axes_shape(axes, axes_num=1, layout=(1, 1))
        self._check_ticks_props(axes, xrot=30)

        tm.close()
        # make sure kwargs to hist are handled
        xf, yf = 20, 18
        xrot, yrot = 30, 40

        axes = grouped_hist(df.A,
                            by=df.C,
                            cumulative=True,
                            bins=4,
                            xlabelsize=xf,
                            xrot=xrot,
                            ylabelsize=yf,
                            yrot=yrot,
                            density=True)
        # height of last bin (index 5) must be 1.0
        for ax in axes.ravel():
            rects = [x for x in ax.get_children() if isinstance(x, Rectangle)]
            height = rects[-1].get_height()
            tm.assert_almost_equal(height, 1.0)
        self._check_ticks_props(axes,
                                xlabelsize=xf,
                                xrot=xrot,
                                ylabelsize=yf,
                                yrot=yrot)

        tm.close()
        axes = grouped_hist(df.A, by=df.C, log=True)
        # scale of y must be 'log'
        self._check_ax_scales(axes, yaxis='log')

        tm.close()
        # propagate attr exception from matplotlib.Axes.hist
        with pytest.raises(AttributeError):
            grouped_hist(df.A, by=df.C, foo='bar')

        with tm.assert_produces_warning(FutureWarning):
            df.hist(by='C', figsize='default')
    def test_grouped_hist_legacy(self):
        from matplotlib.patches import Rectangle

        df = DataFrame(randn(500, 2), columns=['A', 'B'])
        df['C'] = np.random.randint(0, 4, 500)
        df['D'] = ['X'] * 500

        axes = grouped_hist(df.A, by=df.C)
        self._check_axes_shape(axes, axes_num=4, layout=(2, 2))

        tm.close()
        axes = df.hist(by=df.C)
        self._check_axes_shape(axes, axes_num=4, layout=(2, 2))

        tm.close()
        # group by a key with single value
        axes = df.hist(by='D', rot=30)
        self._check_axes_shape(axes, axes_num=1, layout=(1, 1))
        self._check_ticks_props(axes, xrot=30)

        tm.close()
        # make sure kwargs to hist are handled
        xf, yf = 20, 18
        xrot, yrot = 30, 40

        if _mpl_ge_2_2_0():
            kwargs = {"density": True}
        else:
            kwargs = {"normed": True}

        axes = grouped_hist(df.A, by=df.C, cumulative=True,
                            bins=4, xlabelsize=xf, xrot=xrot,
                            ylabelsize=yf, yrot=yrot, **kwargs)
        # height of last bin (index 5) must be 1.0
        for ax in axes.ravel():
            rects = [x for x in ax.get_children() if isinstance(x, Rectangle)]
            height = rects[-1].get_height()
            tm.assert_almost_equal(height, 1.0)
        self._check_ticks_props(axes, xlabelsize=xf, xrot=xrot,
                                ylabelsize=yf, yrot=yrot)

        tm.close()
        axes = grouped_hist(df.A, by=df.C, log=True)
        # scale of y must be 'log'
        self._check_ax_scales(axes, yaxis='log')

        tm.close()
        # propagate attr exception from matplotlib.Axes.hist
        with pytest.raises(AttributeError):
            grouped_hist(df.A, by=df.C, foo='bar')

        with tm.assert_produces_warning(FutureWarning):
            df.hist(by='C', figsize='default')