def work(self, fig=None, ax=None):
        if ax is None:
            if fig is None:
                return fig, ax
            else:
                ax = fig.gca()
        from scipy.stats import gaussian_kde
        x = self.data[self.aes['x']]
        gkde = gaussian_kde(x)
        ind = np.linspace(x.min(), x.max(), 200)
        ax.plot(ind, gkde.evaluate(ind))
        return fig, ax
Draw a one dimensional kernel density plot.
dataset/ETHPy150Open pydata/pandas/pandas/tools/rplot.py/GeomDensity.work