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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 laplacian(f, **kwargs):
 """Calculate the laplacian of a grid of values. Works for both regularly-spaced data, and grids with varying spacing. Either `coordinates` or `deltas` must be specified, or `f` must be given as an `xarray.DataArray` with attached coordinate and projection information. If `f` is an `xarray.DataArray`, and `coordinates` or `deltas` are given, `f` will be converted to a `pint.Quantity` and the gradient returned as a tuple of `pint.Quantity`, otherwise, if neither `coordinates` nor `deltas` are given, the attached coordinate information belonging to `axis` will be used and the gradient will be returned as a tuple of `xarray.DataArray`. Parameters f : array-like Array of values of which to calculate the derivative coordinates : array-like, optional The coordinate values corresponding to the grid points in `f` deltas : array-like, optional Spacing between the grid points in `f`. There should be one item less than the size of `f` along the applicable axis. axes : sequence, optional Sequence of strings (if `f` is a `xarray.DataArray` and implicit conversion to `pint.Quantity` is not used) or integers that specify the array axes along which to take the derivatives. Defaults to all axes of `f`. If given, and used with `coordinates` or `deltas`, its length must be less than or equal to that of the `coordinates` or `deltas` given. Returns ------- array-like The laplacian See Also -------- gradient, second_derivative Notes ----- `laplacian` previously accepted `x` as a parameter for coordinate values. This has been deprecated in 0.9 in favor of `coordinates`. If this function is used without the `axes` parameter, the length of `coordinates` or `deltas` (as applicable) should match the number of dimensions of `f`. """

    pos_kwarg, positions, axes = _process_gradient_args(f, kwargs)
    derivs = [second_derivative(f, axis=axis, **{pos_kwarg: positions[ind]})
              for ind, axis in enumerate(axes)]
    laplac = sum(derivs)
    if isinstance(derivs[0], xr.DataArray):
        # Patch in the units that are dropped
        laplac.attrs['units'] = derivs[0].attrs['units']
    return laplac