def nearest_neighbours(X, Y, norm=2.0):
    """Index the rows of `Y` in increasing order of distance from each row in `X`.

    Parameters
    ----------
    X : array, 2 dimensional, shape = (n_samples, n_dim)
        The matrix, for the rows of which to find the closest row in `Y`.

    Y : array, 2 dimensional, shape = (n_reference, n_dim)
        The matrix, among the rows of which to seek the closest one for `X`.

    norm : float, positive
        The order of the l^p norm to use for computing the pairwise distances.

    Returns
    -------
    index : 2 dimensional
        The matrix of indices of the rows of `Y` for each vector in `X`
        in increasing order of distnace with respect to the l^p norm.

    """
    assert X.ndim == Y.ndim and X.ndim == 2

    ### BEGIN Solution
    indixesY = list(range(0, Y.shape[0]))
    def myfunction(x):
        return list(map(lambda y_i: np.linalg.norm(x - Y[y_i,:], ord=norm), indixesY))

    out = np.argsort(np.apply_along_axis(myfunction, axis=1, arr=X))


    ### END Solution

    return out