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!pip install dimcli networkx pyvis -U --quiet

     |████████████████████████████████| 307kB 8.6MB/s 
     |████████████████████████████████| 51kB 4.3MB/s

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import networkx as nx
from pyvis import network as net
import pyvis
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import scipy
from dimcli.core.extras import NetworkViz

lrst = pd.DataFrame({'class': ['Math', 'Math', 'Math', 'Math','English', 'English', 'English',  'PE', 'PE', 'PE', 'PE', 'History', 'History', 'History', 'History', 'History'],
                    'name': ['Carole ', 'Wood', 'Terrence ', 'Bowen','Anne', 'Singleton', 'Yvette','Edwards', 'Terrence ', 'Foster', 'Austin ','Montgomery', 'Lorena', 'Yvette', 'Kirk', 'Alexander']})
lrst.head(10)

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	class	name
0	Math	Carole
1	Math	Wood
2	Math	Terrence
3	Math	Bowen
4	English	Anne
5	English	Singleton
6	English	Yvette
7	PE	Edwards
8	PE	Terrence
9	PE	Foster

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df = nx.from_pandas_edgelist(lrst, source = 'class', target = 'name')
data = nx.adjacency_matrix(df)
print(data.todense())

[[0 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0]
 [1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
 [1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
 [1 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]
 [1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0]
 [0 0 0 0 0 0 1 1 1 0 0 0 0 0 0 0 0 0]
 [0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]
 [0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0]
 [0 0 0 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0]
 [0 0 0 1 0 0 0 0 0 0 1 1 1 0 0 0 0 0]
 [0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]
 [0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]
 [0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0]
 [0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 1 1]
 [0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]
 [0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]
 [0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]
 [0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0]]

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nodes = list(df.nodes())
documents = lrst['class'].unique().tolist()
names = lrst['name'].unique().tolist()

row_idx = []
for name in names:
      temp = np.where(np.array(nodes) == name)
      row_idx.append(temp[0][0])

col_idx = []
for document in documents:
      temp = np.where(np.array(nodes) == document)
      col_idx.append(temp[0][0])

column_names = lrst['class'].unique().tolist()
doc_matrix = pd.DataFrame(data[np.ix_(row_idx, col_idx)].todense(), columns = column_names)
doc_matrix.insert(0, 'name', pd.Series(names))        
doc_matrix

Out[ ]:

	name	Math	English	PE	History
0	Carole	1	0	0	0
1	Wood	1	0	0	0
2	Terrence	1	0	1	0
3	Bowen	1	0	0	0
4	Anne	0	1	0	0
5	Singleton	0	1	0	0
6	Yvette	0	1	0	1
7	Edwards	0	0	1	0
8	Foster	0	0	1	0
9	Austin	0	0	1	0
10	Montgomery	0	0	0	1
11	Lorena	0	0	0	1
12	Kirk	0	0	0	1
13	Alexander	0	0	0	1

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G = NetworkViz(notebook=True)
G.from_nx(df)
G.show("example.html")

Out[ ]:

None

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