问题描述
我使用sklearn CountVectorizer创建了一个共现矩阵,并将其保存为csv文件。假设它看起来像这样:
Unnamed: 0 a b c d
0 a 0 1 0 0
1 b 2 0 1 0
2 c 0 1 0 3
3 d 0 0 1 0
以该数据帧作为共现矩阵来绘制共现网络的最简单方法是什么?
解决方法
正如@ALollz在评论中提到的那样,您可以使用G=nx.from_pandas_adjacency(df)
从熊猫数据框中创建图形,然后使用pyvis.network
对其进行可视化,如下所示:
import pandas as pd
import numpy as np
import networkx as nx
from pyvis.network import Network
# creating a dummy adjacency matrix of shape 20x20 with random values of 0 to 3
adj_mat = np.random.randint(0,3,size=(20,20))
np.fill_diagonal(adj_mat,0) # setting the diagonal values as 0
df = pd.DataFrame(adj_mat)
# create a graph from your dataframe
G = nx.from_pandas_adjacency(df)
# visualize it with pyvis
N = Network(height='100%',width='100%',bgcolor='#222222',font_color='white')
N.barnes_hut()
for n in G.nodes:
N.add_node(int(n))
for e in G.edges:
N.add_edge(int(e[0]),int(e[1]))
N.write_html('./coocc-graph.html')