How can I convert a two column array to a matrix with counts of occurences?

Question

I have the following numpy array:

import numpy as np

pair_array = np.array([(205, 254), (205, 382), (254, 382), (18, 69), (205, 382), 
                       (31         


        

Answer 1

One way could be to build a graph using NetworkX and obtain the adjacency matrix directly as a dataframe with nx.to_pandas_adjacency. To account for the co-occurrences of the edges in the graph, we can create a nx.MultiGraph, which allows for multiple edges connecting the same pair of nodes:

import networkx as nx

G = nx.from_edgelist(pair_array, create_using=nx.MultiGraph)
nx.to_pandas_adjacency(G, nodelist=sorted(G.nodes()), dtype='int')

      18   31   69   183  205  254  267  382
18     0    0    1    0    0    0    0    0
31     0    0    0    1    0    0    1    1
69     1    0    0    0    0    0    0    0
183    0    1    0    0    0    0    1    1
205    0    0    0    0    0    1    0    2
254    0    0    0    0    1    0    0    1
267    0    1    0    1    0    0    0    0
382    0    1    0    1    2    1    0    0

Building a NetworkX graph, will also enable to create an adjacency matrix or another depending on the behaviour we expect. We can either create it using a:

• nx.Graph: If we want to set to 1 both entries (x,y) and (y,x) for a (x,y) (or (y,x)) edge. This will hence produce a symmetric adjacency matrix
• nx.DiGraph: If (x,y) should only set the (x,y) the entry to 1
• nx.MultiGraph: For the same behaviour as a nx.Graph but accounting for edge co-occurrences
• nx.MultiDiGraph: For the same behaviour as a nx.DiGraph but also accounting for edge co-occurrences