# 和弦图 (Chord Diagram)

# 和弦图创造性地展示了数据点之间复杂的关系。节点围绕一个圆圈排列，通过弧线连接。弧线的长度反映了连接值，其粗细表示关系的重要性。
# 颜色对数据进行分类，使比较变得容易。广泛应用于各个领域，特别是在可视化遗传数据方面。

import holoviews as hv
from holoviews import opts
import pandas as pd
import numpy as np
hv.extension('bokeh')

# Sample matrix representing the export volumes between 5 countries
export_data = np.array([[0, 50, 30, 20, 10],   
                        [10, 0, 40, 30, 20],   
                        [20, 10, 0, 35, 25],   
                        [30, 20, 10, 0, 40],   
                        [25, 15, 30, 20, 0]]) 

labels = ['USA', 'China', 'Germany', 'Japan', 'India']

# Creating a pandas DataFrame
df = pd.DataFrame(export_data, index=labels, columns=labels)
df = df.stack().reset_index()

df.columns = ['source', 'target', 'value']

# Creating a Chord object
chord = hv.Chord(df)

# Styling the Chord diagram
chord.opts(
    opts.Chord(
        cmap='Category20', edge_cmap='Category20', 
        labels='source', label_text_font_size='10pt',  
        edge_color='source', node_color='index', 
        width=700, height=700 
    )
).select(value=(5, None)) 

# Display the plot
chord

📘 5种高级可视化图表/和弦图 (Chord Diagram).ipynb