# Networkx Graph Types

Example of a Mixed graph:. A tree is a connected graph which has no cycles. Currently, most graph neural network models have a somewhat universal architecture in common. A null graph is also called. , graphs in excess of 10 million nodes and 100 million edges. The choice of graph class depends on the structure of the graph you want to represent. Busses are being represented by nodes (Note: only buses with in_service = 1 appear in the graph), edges represent physical connections between buses (typically lines or trafos). This function returns the out-degree for a single node or an iterator for a bunch of nodes or if nothing is passed. Given that correlations are very small, we'll modify each one using the function 1+abs(x))**2, so that they don't look too thin in the graph. Graphs provide a structural model that makes it possible to analyze and understand how many separate systems act together. It's a dictionary where keys are their nodes and values the communities Returns ------- partition : dictionnary The partition,. NetworkX is the most popular Python package for manipulating and analyzing graphs. Get node attributes from graph. NetworkX (NX) is a toolset for graph creation, manipulation, analysis, and visualization. This was inspired by two questions I had: Recently, I have been working with large networks (millions of vertices and edges) and often wonder what is the best currently a. Now, we will discuss the various Special Graphs offered by Networkx module. NX includes a several algorithms, metrics and graph generators. Python language data structures for graphs, digraphs, and multigraphs. python networkx library – quick start guide There are several different types of graphs to represent the relationship between nodes: Undirected graph, Directed graph, Weighted graph, Planar graph, Orthogonal graph, Grid-based graph, etc. Retrieve the zipped archive hw2. Networks can be useful in finding patterns in data and visualizing data clusters. NetWorx Bandwidth monitoring and data usage reports for Windows, macOS and Linux. Max Cohen (played by Sean Gullette, in Pi, a film by Darren Aronofsky). A geometry is an ordered sequence of vertices that are connected by straight line segments or circular arcs. NetworkX: Graph Manipulation and Analysis. This example is probably the most basic network chart you can realise. Plotting networkx graph with node labels defaulting to node name Tag: networkx NetworkX is powerful but I was trying to plot a graph which shows node labels by default and I was surprised how tedious this seemingly simple task could be for someone new to Networkx. Some of the processing that is done on this graph requires me to extract out a specific type of node. Return a NetworkX graph from a Pydot graph. Graph, and plot it with Fruchterman Reingold layout (networkx does not provide the Kamada-Kawai layout). get_default_graph. DiGraph—Directed graphs with self loops. Graphs and Networks 3. Types of Graphs. • This work, to the best of our knowledge, is the first attempt in the literature to combine machine learning and game provenance. In this article, we will be learning the concepts of graphs and graph theory. You can read the networkX documentation, visit their gallery or follow this online course to go further. NetworkX errors while adding nodes: "unhashable type: 'dict'" and "ValueError: too many values to unpack (expected 2)" Ask Question Asked 1 year, 3 months ago. Watch Queue Queue. It provides a number of type clasess, but not an implementation. A graph is a collection of nodes that are connected by links. Barabasi Albert Graph (for Scale Free Models) The current article would deal with the concepts surrounding the complex networks using the python library Networkx. This graph is present in the networkx package. Plotting networkx graph with node labels defaulting to node name Tag: networkx NetworkX is powerful but I was trying to plot a graph which shows node labels by default and I was surprised how tedious this seemingly simple task could be for someone new to Networkx. NetworkX is the most popular Python package for manipulating and analyzing graphs. Return a NetworkX graph from a Pydot graph. How can this graph plot be constructed efficiently (pos?) in Python using networkx? I want to use this for more complicated examples so I feel that hard coding the positions for this simple example won't be useful :(. alpha - The text transparency (default=1. Graph Analysis with Python and NetworkX 2. This was inspired by two questions I had: Recently, I have been working with large networks (millions of vertices and edges) and often wonder what is the best currently a. However, I have a lot of trouble converting this into an actual networkx graph, which I will use for my simulation model. Petersen Graph: The Petersen graph is an undirected graph with 10 vertices and 15 edges. As you'll see, we can include a lot of information in a small space with this type of chart that is also Tableau's answer to those looking for. Once found, click the Install button. save_name: Filename for the plot files in 'save' mode (default: graph. • This work, to the best of our knowledge, is the first attempt in the literature to combine machine learning and game provenance. Note** : Here keywrds is referred to optional keywords that we can mention use to format the graph plotting. I post this as a followup from How to load a weighed shapefile in networkX. So I'm generating a 10x10 matrix using numpy's binomial distribution and use it as a graph matrix. I used read_shp function of the Networkx package to export the directed graph which perfectly matches my needs. In graph theory and network analysis, indicators of centrality identify the most important vertices within a graph. How can I import this networkx Graph G to qQIS for further analysis?. default graph (left), directed graph (right) Python does not have a graph data type. A Graph contains a set of tf. Lab 05: networkx and the analysis of facebook graphs Building and analyzing facebook networks. Graphs and Networks 3. Retrieve the zipped archive hw2. In this article, we will be learning the concepts of graphs and graph theory. As a result, it can quickly and efficiently perform manipulations, statistical analyses of Graphs, and draw them in a visual pleasing style. for representing many types of networks, or graphs, including simple graphs, directed graphs, and graphs with parallel edges and self-loops. To NetworkX Graph¶ Functions to convert NetworkX graphs to and from other formats. NetworkX is a Python language software package for the creation, manipulation, and study of the structure, dynamics, and function of complex networks. So I'm using a networkX graph to represent some information. A pie graph is a circle divided into sections which each display the size of a relative piece of information. Attributes are often associated with nodes and/or edges. NetworkX - create a Graph %time inline in notebook? NetworkX - how to install it? Loading and analyzing data, Datamining. As a result, it can quickly and efficiently perform manipulations, statistical analyses of Graphs, and draw them in a visual pleasing style. Drawing¶ NetworkX provides basic functionality for visualizing graphs, but its main goal is to enable graph analysis rather than perform graph visualization. Networkx provides basic functionality for visualizing graphs, but its main goal is to enable graph analysis rather than perform graph visualization. Python NetworkX. This must be a. All NetworkX graph classes allow (hashable) Python objects as nodes. draw() arguments are the same as networkx. No, there shouldn't be an infinite cycle. With NetworkX you can load and store networks in standard and nonstandard data formats, generate many types of random and classic networks, analyze network structure, build network models, design new network algorithms, draw networks, and much more. Rather than connecting the graph via a configuration model then rewiring to match the intra-community and inter-community degrees, we do this wiring explicitly at the end, which should be equivalent. import networkx from networkx. Graphs and Tables During this unit you will learn about 4 types of Graphs: Bar graph Line graph Circle (Pie) graph Pictograph You will learn about 2 types of … Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. watts_strogatz_graph A great way to explore a python package is to use ipython in interactive mode, then you merely need to type >>from networkx import * watts_strogatz_graph? and you will get the documentation. Installation. We first start by creating a list of edges along with the distances which we will add as the weight of the edge:. A graph is a way of specifying relationships among a collec-tion of items. Although it is very easy to implement a Graph ADT in Python, we will use networkx library for Graph Analysis as it has inbuilt support for visualizing graphs. If graph instance, then cleared before populated. Graph( [ (u,v,d) for u,v,d in G. All NetworkX graph classes allow (hashable) Python objects as nodes and any Python object can be assigned as an edge attribute. draw_networkx_edges. The default function computes the number of shared neighbors. Petersen Graph: The Petersen graph is an undirected graph with 10 vertices and 15 edges. NetworkX graph objects come in different ﬂavors depending on two main properties of the network:. It’s the same as the Insert Chart dialog box. Graph types¶ NetworkX provides data structures and methods for storing graphs. It is widely used in solving graph problems and network related queries. Parameters ---------- graph : networkx. Create networkx graph¶. The rest of the arguments/options are passed as normal arguments / keyword arguments. add_edges_from([("Stallone","Expendables"), ("Schwarzenegger. Just some updates to idiom's for NetworkX specifically. This week I discovered graph-tool, a Python library for network analysis and visualization that is implemented in C++ with Boost. Given a dictionary based graph representation where the keys are nodes and the the values are lists of successor nodes, the code to convert that type of graph representation into a networkx. Positions should be sequences of length 2. A MultiGraph is a simplified representation of a network's topology, reduced to nodes and edges. You should be able to present data accurately even if there are multiple graph types. for representing many types of networks, or graphs, including simple graphs, directed graphs, and graphs with parallel edges and self-loops. Graph in Python A directed graph can be defined as:. Graph Theory The Mathematical study of the application and properties of graphs, originally motivated by the study of games of cha. G (graph) - A networkx graph; pos (dictionary) - A dictionary with nodes as keys and positions as values. draw_options: Graph visual options for networkx. The nodes of the maximal clique graph of G are the cliques of G and an edge joins two cliques if the cliques are not disjoint. get_node_attributes(). This post describes how to use the Python library NetworkX, to deal with network data and solve interesting problems in network analysis. For water networks, the link direction is from the start node to the end node. Network Analysis in Python I NetworkX API basics In [1]: import networkx as nx NETWORK ANALYSIS IN PYTHON Types of graphs. Graph Analysis with Python and NetworkX 2. make_max_clique_graph¶ make_max_clique_graph (G, create_using=None) [source] ¶. nodelist (list, optional) – The rows and columns are ordered according to the nodes in nodelist. Now, we will discuss the various Special Graphs offered by Networkx module. To use the named tuple approach, you’ll need to read the METIS manual for the meanings of the fields. If for every vertex v∈V, deg + (v) = deg − (v), the graph is called a balanced directed graph. This week we will build and analyze facebook networks for undergraduate students at Rice. We've looked at undirected graphs, directed graphs, multi graphs, signed graphs, weighted graphs and so on. If this file contains multiple graphs, only the first such graph is returned. NetworkX includes many graph generator functions and facilities to read and write graphs in many formats. Networkx provides basic functionality for visualizing graphs, but its main goal is to enable graph analysis rather than perform graph visualization. Return type: NetworkX graph. Applications include identifying the most influential person(s) in a social network, key infrastructure nodes in the Internet or urban networks, and super-spreaders of disease. Create networkx graph¶ The basis of all topology functions is the conversion of a padapower network into a NetworkX MultiGraph. Once found, click the Install button. default graph (left), directed graph (right) Python does not have a graph data type. Some of the processing that is done on this graph requires me to extract out a specific type of node. raise TypeError("Input graph is not a networkx graph type") TypeError: Input graph is not a networkx graph type - Jainil Patel Jun 14 at 12:15 @JainilPatel I think you somehow do not have DiGraphs in your networkx package, it works for me - chasmani Jun 14 at 12:29. • This work, to the best of our knowledge, is the first attempt in the literature to combine machine learning and game provenance. In order to use it with python import it, import networkx as nx The following basic graph types are provided as Python classes: Graph This class. Ordered Graphs—Consistently ordered graphs. Contains cities and distance information between them. GML (Graph Modeling Language) is a text file format supporting network data with a very easy syntax. The query must be geocodable and OSM must have polygon boundaries for the geocode result. Thus the above examples clearly define the use of erdos renyi model to make random graphs and how to use the foresaid using the networkx library of python. Gephi is open-source and free. There is an edge between a vertex \(u\) of type B and a vertex \(v\) of type C if the cut-vertex corresponding to \(v\) is in the block corresponding to \(u\). All NetworkX graph classes allow (hashable) Python objects as nodes. We then use Gephi to layout the graph and begin exploring the data. ax (Matplotlib Axes object, optional) - Draw the graph in the specified Matplotlib axes. Networkx is a python package for working with graphs and networks. Drawing¶ NetworkX provides basic functionality for visualizing graphs, but its main goal is to enable graph analysis rather than perform graph visualization. Welcome to the world of Graphs. Possible values include graph, node, edge, and all. Wind Rose and Polar Bar Charts. com wrote:. Become a graph and social analyst today. py make a class for each type. The choice of graph class depends on the structure of the graph you want to represent. Parameters graph networkxgraph the networkx graph. Python language data structures for graphs, digraphs, and multigraphs. Q&A for Work. MultiGraph—Undirected graphs with self loops and parallel edges. Make some minor adjustments and you have the slide I showed at the top of this post. Degree sequence. graph: networkx. 0+ version of NetworkX, Python3, and for my own purposes I converted to utf-8 instead of ascii for international usages. One examples of a network graph with NetworkX. Social Network Analysis using PatentsView and NetworkX By Jesse Frumkin and Amanda Myers August 28, 2017 The InventorAnalyze package is a powerful new tool for bibliometric (and other) researchers studying the social network of inventors, i. edge, which is a nested dictionary. ; As the library is purely made in python, this fact makes it highly scalable, portable and reasonably efficient at the same time. NetworkX + VTK + ParaView. NetworkX is suitable for operation on large real-world graphs: e. Hypothesis-networkx. the algorithm will start using this partition of the nodes. read_dot (path) Returns a NetworkX graph from a dot file on path. The domain of the GraphML-Attribute specifies for which graph elements the GraphML-Attribute is declared. What are the essential data Gephi is looking for in a graph file? We distinguish tree types of data: nodes, edges and attributes. The directed graph realization problem is the problem of finding a directed graph with the degree sequence a given sequence of positive integer pairs. In graph theory and network analysis, indicators of centrality identify the most important vertices within a graph. See here to see the different possibilities. Type of objective. Become a graph and social analyst today. Yes, JUNG supports dynamic graphs that can be changed both through a system of filters or by explicitly adding and removing nodes. So insteading of typing networkx from now on, we will use the abbreviation nx. It is a Python language software package for the creation, manipulation, and study of the structure, dynamics, and function of complex networks. create_using (NetworkX graph) - Use specified graph for result. This video is unavailable. Directed Graphs, Undirected Graphs, and Weighted Graphs along with a gist of relation depiction through edges. the start state together with states that may be involved in positively matching a string (reachable from the start node and an ancestor of an accepting node). Yes, networkx is well integrated with scipy and numpy and uses efficient data structures for algorithms that require intensive computation. Each section of the graph comes together to form a whole. It provides a number of type clasess, but not an implementation. Because networkx cannot read. Usually used to set the type of the graph. The preferred way of converting data to a NetworkX graph is through the graph constuctor. How to make Network Graphs in Python with Plotly. Returns: Graph - A graph that is the projection onto the given nodes. 7 MB) File type Source Python version None Upload date Apr 11, 2019 Hashes View hashes. The type of NetworkX graph generated by WNTR is a directed multigraph. Our solution: NetworkX + VTK + ParaView. Parameters label_image array of int. Learn Graphs and Social Network Analytics. NetworkX is a Python language software package for the creation, manipulation, and study of the structure, dynamics, and function of complex networks. Welcome to the Python Graph Gallery. Networkx provides basic functionality for visualizing graphs, but its main goal is to enable graph analysis rather than perform graph visualization. Some of the general graph layouts are : draw_circular(G, keywrds) : This gives cicular layout of the graph G. You should note that the NetworkX package also supports MultiGraph() and MultiDiGraph() graph types. You can use different types of line using the style argument. tname, _, key = get_prop_type(val, key) in NetworkX a node can be any hashable type, but. NetworkX graph objects come in different flavors depending on two main properties of the network:. It is a small graph that serves as a useful example and counterexample for many problems in graph theory. The basis of all topology functions is the conversion of a padapower network into a NetworkX MultiGraph. A network chart is constituted by nodes. Nodes are part of the attribute Graph. NetworkX Developers. Here’s a cartoon that shows off the import directive in Python. You can vote up the examples you like or vote down the ones you don't like. Note** : Here keywrds is referred to optional keywords that we can mention use to format the graph plotting. A graph (network) is a collection of nodes together with a collection of edges that are pairs of nodes. The degree sequence of a directed graph is the list of its indegree and outdegree pairs; for the above example we have degree sequence ((2, 0), (2, 2), (0, 2), (1, 1)). NetworkX errors while adding nodes: "unhashable type: 'dict'" and "ValueError: too many values to unpack (expected 2)" Ask Question Asked 1 year, 3 months ago. Get node attributes from graph. Graph (abstract data type) These pairs are known as edges, arcs, or lines for an undirected graph and as arrows, directed edges, directed arcs, or directed lines for a directed graph. NetworkX errors while adding nodes: “unhashable type: 'dict'” and “ValueError: too many values to unpack (expected 2)” Ask Question Asked 1 year, 3 months ago. Pygraphviz is a Python interface to the Graphviz graph layout and visualization package. A random network is more formally termed the Erdős–Rényi random graph model, so named after two mathematicians who first introduced a set of models for random graphs in the mid 20th century. Let us start with an example graph which we are using for our purpose. So, in the past videos we've looked at different types of graphs. Two types of ultrasonographic measurements are used: (1) The time-amplitude or A-scan which measures the time or distance from the transducer to the interface and back. This algorithm differs slightly from the original way it was presented in [1]. The previous comment's link seems to be dead, so this is a quick note to any who follow that I made a few tweaks to make this work with a 2. The default function computes the number of shared neighbors. The first choice to be made when using NetworkX is what type of graph object to use. With NetworkX you can load and store networks in standard and nonstandard data formats, generate many types of random and classic networks, analyze network structure, build network models, design new network algorithms, draw networks, and much more. The rest of the arguments/options are passed as normal arguments / keyword arguments. A graph is a way of specifying relationships among a collec-tion of items. Edges are part of the attribute Graph. A NetworkX network is a collection of edges and labeled nodes. This little project defines a function that can be used to construct a Cypher query which when executed against a Neo4j database server will store the graph to the server. networkx Graph Library –To check if you have it installed, type “import networkx” in the python interpreter in Canopy (nothing should happen, but if it is. Currently, most graph neural network models have a somewhat universal architecture in common. So I'm using a networkX graph to represent some information. RAG (label_image=None, connectivity=1, data=None, **attr) [source] ¶ Bases: networkx. We haven't looked at a particular type of graph that is very interesting and useful for certain types of applications, and these are called bipartite graphs. A graph (network) is a collection of nodes together with a collection of edges that are pairs of nodes. Q&A for Work. add_edges_from([("Stallone","Expendables"), ("Schwarzenegger. Note** : Here keywrds is referred to optional keywords that we can mention use to format the graph plotting. A lobster is a tree that reduces to a caterpillar when pruning all leaf nodes. networkx documentation: Installation or Setup. With NetworkX you can load and store networks in standard and nonstandard data formats, generate many types of random and classic networks, analyze network structure, build network models, design new network algorithms, draw networks, and much more. Converts a pandapower network into a NetworkX graph, which is a is a simplified representation of a network's topology, reduced to nodes and edges. edge, which is a nested dictionary. NetworkX Tutorial Jacob Bank (adapted from slides by Evan Rosen) Graph Types Graph : Undirected simple (allows self loops) located in module networkx. WNTR uses NetworkX data objects to store network connectivity as a graph. So I have created a network with QGIS and OSM (openstreetmaps), and exported it into two files: nodes and edges using of shapefiles. So, in the past videos we've looked at different types of graphs. In this post I benchmark the performance of 5 popular graph/network packages. Yes, JUNG supports dynamic graphs that can be changed both through a system of filters or by explicitly adding and removing nodes. User interface is through scripting/command-line provided by Python. Attempt to construct the same minimum spanning tree, and if the edge that was removed was part of the spanning tree, grab the next smallest edge. This week we will build and analyze facebook networks for undergraduate students at Rice. All NetworkX graph classes allow (hashable) Python objects as nodes. This example is probably the most basic network chart you can realise. zip from Owlspace and save it in your comp140 folder. The following articles will be using the latest version 2. create_using (NetworkX graph) - Use specified graph for result. This was inspired by two questions I had: Recently, I have been working with large networks (millions of vertices and edges) and often wonder what is the best currently a. NetWorx is a simple, yet versatile and powerful tool that helps you objectively evaluate your bandwidth consumption situation. Return type: NetworkX graph. png, graph_1. Networkx allow us to study the network structure and provides several analysis measures. di*****@gmail. Possible values include graph, node, edge, and all. A graph is a set of nodes or vertices, connected together by edges. networkx is a python module that allows you to build networks (or graphs). The docstrings include educational information about each named graph with the hopes that this class can be used as a reference. A graph consists of a set of objects, called nodes, with certain pairs of these objects connected by links called edges. Otherwise a new graph is created. Type "graphs. This video is unavailable. Thus echoes from surfaces deeper within the eye take longer to return to the transducer for conversion into electrical potential and so they appear further along the time base. Create networkx graph¶ The basis of all topology functions is the conversion of a padapower network into a NetworkX MultiGraph. For instance, caller-callee relationships in a computer program can be seen as a graph (where cycles indicate recursion, and unreachable nodes represent dead code). Attributes are often associated with nodes and/or edges. Graph (abstract data type) These pairs are known as edges, arcs, or lines for an undirected graph and as arrows, directed edges, directed arcs, or directed lines for a directed graph. Parameters ---------- graph : networkx. Now, we will discuss the various Special Graphs offered by Networkx module. Do you have a use for this type of chart? Share your experiences with charts that have 2 chart types and 2 Y-axes. Return type: NetworkX graph. , data center or switch. tname, _, key = get_prop_type(val, key) in NetworkX a node can be any hashable type, but. New to Plotly? Plotly's R library is free and open source! Get started by downloading the client and reading the primer. Its functioning is well described in its dedicated datacamp course. I guess it's possible that they can't be run; at least something seems to want Gtk which would imply X. out_degree (nbunch=None, weight=None) [source] ¶ Return an iterator for (node, out-degree) or out-degree for single node. Where a smaller lower addition is added to a building, the new roof makes one continuous roof with the main roof, and is often at a shallower pitch to the main roof. Graph analysis is not a new branch of data science, yet is not the usual "go-to" method data scientists apply today. This example is probably the most basic network chart you can realise. Examples Installation or Setup Welcome to the world of Graphs. The Graph Driver consists of APIs for graph CRUD operations (add/remove vertex, add/remove edge, etc. DiGraph (directed graph) object is:. We first start by creating a list of edges along with the distances which we will add as the weight of the edge:. I guess it's possible that they can't be run; at least something seems to want Gtk which would imply X. Hide the Output. Convert Dictionary Graph Representation into networkx Graph Representation. Jump to navigation. Introduction. In this post I benchmark the performance of 5 popular graph/network packages. Graph in Python A directed graph can be defined as:. pyplot as plt # importing matplotlib package and pyplot is for displaying the graph on canvas b=nx. Now, we will discuss the various Special Graphs offered by Networkx module. We will then work on a case study to solve a commonly seen problem in the aviation industry by applying the concepts of Graph Theory using Python. Every time I need to do this, I do something along the lines of the code below. add_edges_from([("Stallone","Expendables"), ("Schwarzenegger. DiGraph—Directed graphs with self loops. zip from Owlspace and save it in your comp140 folder. Visited and unvisited nodes in the graph are kept track of, and a visited node will never be visited again. Current known types are: any NetworkX graph: dict-of-dicts: dict-of-lists: list of edges: Pandas DataFrame (row per edge) numpy matrix: numpy ndarray: scipy sparse matrix: pygraphviz agraph: create_using : NetworkX graph constructor, optional (default=nx. watts_strogatz_graph A great way to explore a python package is to use ipython in interactive mode, then you merely need to type >>from networkx import * watts_strogatz_graph? and you will get the documentation. The preferred way of converting data to a NetworkX graph is through the graph constuctor. Attempt to construct the same minimum spanning tree, and if the edge that was removed was part of the spanning tree, grab the next smallest edge. Next we will discuss the ego graph and various other types of graphs in python using the library networkx. Graph types ¶ NetworkX provides data structures and methods for storing graphs. , the community of inventors who collaborated on jointly invented patents. A Simple d3 Network Graph. NetworkX graph objects come in different flavors depending on two main properties of the network:. default graph (left), directed graph (right) Python does not have a graph data type. The choice of graph class depends on the structure of the graph you want to represent. Its functioning is well described in its dedicated datacamp course. NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. NetworkX graph objects come in different ﬂavors depending on two main properties of the network:. Become a graph and social analyst today. Like this numpy sparse matrix that Networkx uses as the adjacency matrix for our binary tree:. This graph is present in the networkx package. DiGraph—Directed graphs with self loops. Classic use cases range from fraud detection, to recommendations, or social network analysis. You can vote up the examples you like or vote down the ones you don't like. The library allows you to use any hashable Python data as a node label (different labels within the same graph may belong to different data types). A graph (network) is a collection of nodes together with a collection of edges that are pairs of nodes. The ﬁrst choice to be made when using NetworkX is what type of graph object to use. How can I import this networkx Graph G to qQIS for further analysis?. ax (Matplotlib Axes object, optional) - Draw the graph in the specified Matplotlib axes. A MultiGraph is a simplified representation of a network's topology, reduced to nodes and edges. draw(b) #draws the networkx graph. If this file contains multiple graphs, only the first such graph is returned. All NetworkX graph classes allow (hashable) Python objects as nodes and any Python object can be assigned as an edge attribute.