GeoDataFrame extends the functionality of pandas to deal with spatial data. They have special features and functions that are useful in Geographic Information Systems (GIS). In this article, we will see how we can convert MultiDiGraph to GeoDataFrame using OSMnx module.

Syntax of osmnx.utils_graph.graph_to_gdfs() Function

OSMnx utils_graph module (graph_to_gdfs) facilitates the conversion of MultiDiGraph (node/edge) to GeoDataFrames. The OSMnx functionality is as follows:

osmnx.utils_graph.graph_to_gdfs(G, nodes=True, edges=True, node_geometry=True, fill_edge_geometry=True)

Parameters

• G (networkx.MultiDiGraph) – input graph
• nodes (bool) – if True, convert graph nodes to a GeoDataFrame and return it
• edges (bool) – if True, convert graph edges to a GeoDataFrame and return it
• node_geometry (bool) – if True, create a geometry column from node x and y attributes
• fill_edge_geometry (bool) – if True, fill in missing edge geometry fields using nodes u and v

Returns

gdf_nodes or gdf_edges or tuple of (gdf_nodes, gdf_edges). gdf_nodes is indexed by osmid and gdf_edges is multi-indexed by u, v, key following normal MultiDiGraph structure.

Return Type

geopandas.GeoDataFrame or tuple

Getting Sample MultiDiGraph

Now let’s get into the implementation. Here we need an input graph, which is of type MultiDiGraph. We can get it by giving the address to osmnx module, graph_from_place. The code is shown below.

import osmnx as ox

multi_digraph = ox.graph_from_place('Modena, Italy')
multi_digraph

Output

<networkx.classes.multidigraph.MultiDiGraph at 0x178933df040>

We can get a better idea by plotting it. 

ox.plot_graph(multi_digraph)

Output

plot multidigraph

Fetch the nodes

multi_digraph.nodes

Output

NodeView((60718257, 60718342, 60718350, 60718497, 60718657, 60718674, 60718691, 60718698, 60718705, 60718711, 60718717, 60718718, 60718740, 60718759, 60718778, 60718794, 82553388, 82553402, 82553405, 82553406, 82553410, 82553411, 82553416, 82553434, …… ))

Fetch the edges

multi_digraph.edges

Output

OutMultiEdgeView([(60718257, 60718350, 0), (60718257, 1786966488, 0), (60718342, 7048889484, 0), (60718342, 60718350, 0), (60718342, 8853584243, 0), (60718350, 60718257, 0), (60718350, 1786966480, 0), (60718350, 60718342, 0), (60718497, 60718794, 0), ….])

Convert MultiDiGraph to GeoDataFrame Using OSMnx utils_graph Module

Now you have a basic idea about the generated MultiDigraph. It’s time to make use of OSMnx functionality to convert multidigraph to geodataframe. We can extract nodes, edges or both as geodataframe using the graph_to_gdfs functionality. Let’s convert both nodes and edges together. The code as follows:

import osmnx as ox

# fetch nodes and edges as geodataframe

geo_dataframe = ox.utils_graph.graph_to_gdfs(
    multi_digraph, nodes=True, edges=True,
    node_geometry=False, fill_edge_geometry=False)

# print geodataframe in notebook
geo_dataframe

Output

Geodataframe (nodes and edges)

In the above example, we fetched both nodes and edges by setting the required params as True (nodes and edges). The below code extracts nodes and its corresponding geometry.

# fetch nodes with geometry
geo_dataframe_node = ox.utils_graph.graph_to_gdfs(
    multi_digraph, nodes=True, edges=False, node_geometry=True,
    fill_edge_geometry=False)

# print in jupyter notebook
geo_dataframe_node

Output

Geodataframe – Nodes with geometry

As a next step we extract edges as geodataframe, by setting edge parameter as True.

# convert edges to geodataframe
geodf_edge = ox.utils_graph.graph_to_gdfs(
    multi_digraph, nodes=False, edges=True, node_geometry=False,
    fill_edge_geometry=True)

Output

Edges as Geodataframe

Let’s check the type of the generated output

type(geodf_edge)

Output

geopandas.geodataframe.GeoDataFrame

We can review the generated geodataframe edges in map using geopandas.

# project it in map
geodf_edge.explore()

Output

geodataframe in a map