The NeighborsSubgraph class in the hana_ml.graph.algorithms.neighbors module provides a method to get a subset of a graph based on a start vertex and all vertices within a specified range of degrees of separation, including edges between neighbors, which can be useful for visualization.
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Here is a Python code template based on the provided help doc:

```python
import hana_ml.graph.algorithms as hga

class NeighborsSubgraph(hga._NeighborsBase):
    def __init__(self, graph):
        super().__init__(graph)

    def execute(self, start_vertex, direction='OUTGOING', lower_bound=1, upper_bound=1):
        # Executes the calculation of the neighbors with edges.
        pass

    @property
    def edges(self):
        # Returns a Pandas DataFrame that contains the edges between neighbors
        pass

    @property
    def vertices(self):
        # Returns a Pandas DataFrame that contains the vertices
        pass

    @staticmethod
    def projection_expr_from_cols(source, variable, column_filter=None):
        # Turn columns into a string for projection expression
        pass

    @staticmethod
    def signature_from_cols(source, column_filter=None):
        # Turn columns into a string for script parameters
        pass

# Usage
# Assuming 'g' is a graph object
nb = NeighborsSubgraph(graph=g).execute(start_vertex="1")
print("Vertices", nb.vertices)
print("Edges", nb.edges)
```

Please note that this is a template and the actual implementation of the methods is not provided. You need to replace the `pass` statements with your own code.