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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 get_grid_data(xall, yall, zall, nbins=100, method='nearest'):
 """Interpolate unstructured two-dimensional data. Parameters xall : ndarray(T) Sample x-coordinates. yall : ndarray(T) Sample y-coordinates. zall : ndarray(T) Sample z-coordinates. nbins : int, optional, default=100 Number of histogram bins used in x/y-dimensions. method : str, optional, default='nearest' Assignment method; scipy.interpolate.griddata supports the methods 'nearest', 'linear', and 'cubic'. Returns ------- x : ndarray(nbins, nbins) The bins' x-coordinates in meshgrid format. y : ndarray(nbins, nbins) The bins' y-coordinates in meshgrid format. z : ndarray(nbins, nbins) Interpolated z-data in meshgrid format. """

    from scipy.interpolate import griddata
    x, y = _np.meshgrid(
        _np.linspace(xall.min(), xall.max(), nbins),
        _np.linspace(yall.min(), yall.max(), nbins),
        indexing='ij')
    z = griddata(
        _np.hstack([xall[:,None], yall[:,None]]),
        zall, (x, y), method=method)
    return x, y, z