def project_graph(G, to_crs=None):
    """
    Project a graph from lat-long to the UTM zone appropriate for its geographic
    location.

    Parameters
    ----------
    G : networkx multidigraph
        the networkx graph to be projected
    to_crs : dict
        if not None, just project to this CRS instead of to UTM

    Returns
    -------
    networkx multidigraph
    """

    G_proj = G.copy()
    start_time = time.time()

    # create a GeoDataFrame of the nodes, name it, convert osmid to str
    nodes, data = zip(*G_proj.nodes(data=True))
    gdf_nodes = gpd.GeoDataFrame(list(data), index=nodes)
    gdf_nodes.crs = G_proj.graph['crs']
    gdf_nodes.gdf_name = '{}_nodes'.format(G_proj.name)

    # create new lat/lon columns just to save that data for later, and create a
    # geometry column from x/y
    gdf_nodes['lon'] = gdf_nodes['x']
    gdf_nodes['lat'] = gdf_nodes['y']
    gdf_nodes['geometry'] = gdf_nodes.apply(lambda row: Point(row['x'], row['y']), axis=1)
    log('Created a GeoDataFrame from graph in {:,.2f} seconds'.format(time.time()-start_time))

    # project the nodes GeoDataFrame to UTM
    gdf_nodes_utm = project_gdf(gdf_nodes, to_crs=to_crs)

    # extract data for all edges that have geometry attribute
    edges_with_geom = []
    for u, v, key, data in G_proj.edges(keys=True, data=True):
        if 'geometry' in data:
            edges_with_geom.append({'u':u, 'v':v, 'key':key, 'geometry':data['geometry']})

    # create an edges GeoDataFrame and project to UTM, if there were any edges
    # with a geometry attribute. geom attr only exists if graph has been
    # simplified, otherwise you don't have to project anything for the edges
    # because the nodes still contain all spatial data
    if len(edges_with_geom) > 0:
        gdf_edges = gpd.GeoDataFrame(edges_with_geom)
        gdf_edges.crs = G_proj.graph['crs']
        gdf_edges.gdf_name = '{}_edges'.format(G_proj.name)
        gdf_edges_utm = project_gdf(gdf_edges, to_crs=to_crs)

    # extract projected x and y values from the nodes' geometry column
    start_time = time.time()
    gdf_nodes_utm['x'] = gdf_nodes_utm['geometry'].map(lambda point: point.x)
    gdf_nodes_utm['y'] = gdf_nodes_utm['geometry'].map(lambda point: point.y)
    gdf_nodes_utm = gdf_nodes_utm.drop('geometry', axis=1)
    log('Extracted projected node geometries from GeoDataFrame in {:,.2f} seconds'.format(time.time()-start_time))

    # clear the graph to make it a blank slate for the projected data
    start_time = time.time()
    edges = list(G_proj.edges(keys=True, data=True))
    graph_name = G_proj.graph['name']
    G_proj.clear()

    # add the projected nodes and all their attributes to the graph
    G_proj.add_nodes_from(gdf_nodes_utm.index)
    attributes = gdf_nodes_utm.to_dict()
    for label in gdf_nodes_utm.columns:
        nx.set_node_attributes(G_proj, name=label, values=attributes[label])

    # add the edges and all their attributes (including reconstructed geometry,
    # when it exists) to the graph
    for u, v, key, attributes in edges:
        if 'geometry' in attributes:
            row = gdf_edges_utm[(gdf_edges_utm['u']==u) & (gdf_edges_utm['v']==v) & (gdf_edges_utm['key']==key)]
            attributes['geometry'] = row['geometry'].iloc[0]

        # attributes dict contains key, so we don't need to explicitly pass it here
        G_proj.add_edge(u, v, **attributes)

    # set the graph's CRS attribute to the new, projected CRS and return the
    # projected graph
    G_proj.graph['crs'] = gdf_nodes_utm.crs
    G_proj.graph['name'] = '{}_UTM'.format(graph_name)
    if 'streets_per_node' in G.graph:
        G_proj.graph['streets_per_node'] = G.graph['streets_per_node']
    log('Rebuilt projected graph in {:,.2f} seconds'.format(time.time()-start_time))
    return G_proj
Project a graph from lat-long to the UTM zone appropriate for its geographic
    location.

    Parameters
    ----------
    G : networkx multidigraph
        the networkx graph to be projected
    to_crs : dict
        if not None, just project to this CRS instead of to UTM

    Returns
    -------
    networkx multidigraph