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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def plot_residuals(self, plot=None):
 """ Plot normalized fit residuals. The sum of the squares of the residuals equals ``self.chi2``. Individual residuals should be distributed about one, in a Gaussian distribution. Args: plot: :mod:`matplotlib` plotter. If ``None``, uses ``matplotlib.pyplot`. Returns: Plotter ``plot``. """

        if plot is None:
            import matplotlib.pyplot as plot
        x = numpy.arange(1, len(self.residuals) + 1)
        y = _gvar.mean(self.residuals)
        yerr = _gvar.sdev(self.residuals)
        plot.errorbar(x=x, y=y, yerr=yerr, fmt='o', color='b')
        plot.ylabel('normalized residuals')
        xr = [x[0], x[-1]]
        plot.plot([x[0], x[-1]], [0, 0], 'r-')
        plot.fill_between(
            x=xr, y1=[-1,-1], y2=[1,1], color='r', alpha=0.075
            )
        return plot