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import networkx as nximport matplotlib.pyplot as plt
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# Create an undirected graph GG = nx.Graph()print("graph G is directed: {}".format(G.is_directed()) )
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# Create a directed graph HH = nx.DiGraph()print("graph H is directed: {}".format(H.is_directed()) )
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#getting the number of edges and nodesG.number_of_nodes(), G.number_of_edges()
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#adding nodeG.add_node(1)G.add_nodes_from([2, 3])# we can add from another graph H = nx.path_graph(3)G.add_nodes_from(H)#or directly a graphG.add_node(H)G.number_of_nodes(), G.number_of_edges()
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#adding edgesG.add_edge(1, 2)e = (2, 3)G.add_edge(e)G.add_edges_from([(1, 2), (1, 3)])G.add_edges_from(H.edges())
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# Create an undirected graph GG = nx.Graph() #it is empty# Add first node with node level attributesG.add_node(0, feature=3, label=0)
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# Get attributes of the node 0attr = G.nodes[0]print("Node 0 has the attributes {}".format(attr))
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# You can add multiple nodes with attributes#a list, providing a tuple (node, dict(feat1, feat2..))G.add_nodes_from([  (1, {"feature": 1, "label": 1}),  (2, {"feature": 2, "label": 2})])
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# we can loop through the nodes # argument data = True to return attributesfor node in G.nodes(data=True):  print(node)
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# Get number of nodesn_nodes = G.number_of_nodes()print("G has {} nodes".format(n_nodes))
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# Add one edge with edge weight 0.5G.add_edge(0, 1, weight=0.5)
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# Get attributes of the edge (0, 1)edge_0_1_attr = G.edges[(0, 1)]print("Edge (0, 1) has the attributes {}".format(edge_0_1_attr))
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# Add multiple edges with edge weightsG.add_edges_from([  (1, 2, {"weight": 0.3}),  (2, 0, {"weight": 0.1})])
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# Loop through all the edges# Here there is no data=True, so only the edge will be returnedfor edge in G.edges():  print(edge)
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# Get number of edgesnum_edges = G.number_of_edges()print("G has {} edges".format(num_edges))
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# Draw the graphnx.draw(G, with_labels = True)

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!pip install igraph!apt install libcairo2-dev!pip install pycairo
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from igrpaph import *#print(igraph.__version__)
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#creating a graph from scratchg = Graph()#add verticesg.add_vertices(3)#add egdgesg.add_edges([(0,1), (1,2)])#check the graphprint(g)
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g.vs["label"] = g.vs["name"]color_dict = {"m": "blue", "f": "pink"}g.vs["color"] = [color_dict[gender] for gender in g.vs["gender"]]plot(g, layout=layout, bbox=(300, 300), margin=20)