<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def degree_prune(graph, max_degree=20):
 """Prune the k-neighbors graph back so that nodes have a maximum degree of ``max_degree``. Parameters graph: sparse matrix The adjacency matrix of the graph max_degree: int (optional, default 20) The maximum degree of any node in the pruned graph Returns ------- result: sparse matrix The pruned graph. """


    result = graph.tolil()
    for i, row_data in enumerate(result.data):
        if len(row_data) > max_degree:
            cut_value = np.argsort(row_data)[max_degree]
            row_data = [x if x <= cut_value else 0.0 for x in row_data]
            result.data[i] = row_data
    result = result.tocsr()
    result.eliminate_zeros()
    return result