绘制节点度数直方图 (networkx)

Question

我有一个用 networkx 创建的网络。

我想查看网络中所有节点与同一网络中特定节点的分布情况。

我创建了两个节点度数的字典如下：

df = df.T.corr(method="spearman")


edges = df.stack().reset_index()
edges.columns = ['var_1','var_2','correlation']
edges = edges.loc[ (edges['correlation'] < -0.6) | (edges['correlation'] > 0.6) & (edges['var_1'] != edges['var_2']) ].copy()

#create undirected graph with weights corresponding to the correlation magnitude
G0 = nx.from_pandas_edgelist(edges, 'var_1', 'var_2', edge_attr=['correlation'])


print(nx.info(G0))

# =============================================================================
degrees = [val for (node, val) in G0.degree()]
degrees2 = [val for (node, val) in G0.degree(['Aureobasidium', 'Cladosporium', 'Alternaria',
                                              'Filobasidium', 'Vishniacozyma',
                                              'Sporobolomyces', 'Sphingomonas',
                                              'Methylobacterium'])]

如何在一个简单的条形图上表示节点的度数（两个条形彼此相邻）当Y轴为每一度数，X轴为度数时

我找到了这段代码：https://networkx.github.io/documentation/stable/auto_examples/drawing/plot_degree_histogram.html 这就是我想要的，没有小网络。

我知道了

虽然我希望条形图彼此相邻

任何halp都会很感激！谢谢！

Answer 1

这是随机图的演示图。

import numpy as np
import networkx as nx
import matplotlib.pyplot as plt

G = nx.fast_gnp_random_graph(100, .5)
degrees = [val for (node, val) in G.degree()]
degrees2 = [abs(d - 1) for d in degrees]

d1 = np.array(degrees)
d2 = np.array(degrees2)

plt.hist([d1, d2], label=['d1', 'd2'])
plt.legend(loc='upper right')
plt.show()

绘制节点度数直方图 (networkx)

ploting histogram of node degrees (networkx)

python

matplotlib

networkx