【问题标题】:Plotting a graph in Python with Values在 Python 中使用值绘制图形
【发布时间】:2021-04-17 14:57:32
【问题描述】:

我试图在图表上的箭头上显示诸如“更宽”、“更窄”之类的值,但我不知道该怎么做。我已经阅读了之前的帖子,例如 how to draw directed graphs using networkx in python? 并阅读了 NetworkX 的文档 (https://networkx.org/documentation/latest/_downloads/networkx_reference.pdf),但我无法实现。

下面提到了我的代码;

# libraries
import pandas as pd
import numpy as np
import networkx as nx
import matplotlib.pyplot as plt
 
# Build a dataframe with your connections
df = pd.DataFrame({ 'from':['Plankton', 'Plankton', 'Plankton', 'Plankton', 'Plankton', 'Plankton', 'Plankton'], 'to':['aquatic communities', 'plankton surveys', 'zooplankton','phytoplankton', 'cryoplankton', 'nannoplankton', 'picoplankton'], 'value':['broader', 'related', 'narrower', 'narrower','narrower','narrower','narrower']}) 
# And I need to transform my categorical column in a numerical value typeA->1, typeB->2...
df['value']=pd.Categorical(df['value'])
df['value'].cat.codes
 
# Build your graph
G=nx.from_pandas_edgelist(df, 'from', 'to', create_using=nx.DiGraph(directed=True) )
 
# Custom the nodes:

nx.draw_networkx(G, font_size = 10, with_labels=True, arrows=True, node_color= 'skyblue', node_size= 500, width= 3.5, arrowstyle= '-|>', arrowsize= 12, edge_color=df['value'].cat.codes)

【问题讨论】:

    标签: python pandas numpy graph networkx


    【解决方案1】:

    您可以使用draw_networkx_edge_labels() 绘制边缘标签。

    G = nx.from_pandas_edgelist(df, 'from', 'to', create_using=nx.DiGraph(directed=True) )
    
    pos = nx.spring_layout(G)
    
    nx.draw_networkx(G, pos, font_size = 10, with_labels=True, arrows=True, node_color= 'skyblue', node_size= 500, width= 3.5, arrowstyle= '-|>', arrowsize= 12, edge_color=df['value'].cat.codes)
    
    nx.draw_networkx_edge_labels(G,pos,edge_labels=dict(zip(G.edges, df['value'].tolist())))
    
    plt.show()
    

    它有额外的可选参数label_pos 供您调整标签在边缘的位置。

    • 0:头
    • 0.5:中心
    • 1:尾

    也支持0、1之间的其他浮点数。

    【讨论】:

      猜你喜欢
      • 2021-10-28
      • 1970-01-01
      • 1970-01-01
      • 1970-01-01
      • 2017-03-12
      • 1970-01-01
      • 1970-01-01
      • 2020-11-04
      • 1970-01-01
      相关资源
      最近更新 更多