在Python中为Sankey Diagram添加图例

如何解决在Python中为Sankey Diagram添加图例

我当前的输出是这样的：

我想添加一个图例，因为您看到每种不同的颜色都有不同的范围，所以我想要一个图例：

Blue Line :   (      0,10000 )
Red Line :    (  10001,100000 )
Yellow Line : ( 100001,500000 )

我的Sankey图表代码是：

import alluvial,csv,os
from   ipysankeywidget import SankeyWidget
import pySankey
from   pySankey import sankey
import matplotlib.pyplot as plt
import matplotlib.cm
%matplotlib inline
import pandas as pd
pd.options.display.max_rows=8
from   operator import itemgetter
import networkx as nx
from   networkx.algorithms import community #This part of networkx,for community detection,import numpy as np
import pandas as pd

database = pd.read_excel('network_analisis.xlsx',sheet_name = 'Data')
classification = pd.read_excel('Classifcation.xlsx')
a = classification['Country'].unique().tolist() 
b = database['Countries'].unique().tolist()  
matches = [x for x in a if x in b]
not_matches = [x for x in a if x not in b]
classification1 = classification
for a in classification1['Country']:
    for b in not_matches:
        if a == b:
           classification1 = classification1.drop(classification1[classification1.Country == a].index)
database_1 = database.merge(classification1,left_on='Countries',right_on='Country')
del database_1['RES']
del database_1['TOT']
database_1['Range'] = 0 
for i in range(len(database_1['Countries'])):
     if database_1['USD'][i] <= 10000:
            database_1['Range'][i] = '[0,10000]'
     elif database_1['USD'][i] > 10000 and database_1['USD'][i] <= 100000 :
            database_1['Range'][i] = '[10001,100000]'  
     elif database_1['USD'][i] > 100001 and database_1['USD'][i] <= 500000 :
            database_1['Range'][i] = '[100001,500000]'    
            


datanuueva = database_1.melt(id_vars=["Countries",'Country','Code','ISO','Region (IMF)','Region (WB)','IMF Regional Technical Assistance Center (R-TAC)','Exchange Arrangement Classification','Market Type (IMF)','Income Level (World Bank) 2018','Monetary Union','Range'],var_name="Currencies",value_name="Values")
datanuueva.sort_values(by=['Countries'],inplace =True)
datanuueva1 = datanuueva[datanuueva['Countries'] != 'Total' ]
datanuueva2 = datanuueva1[datanuueva1['Values'] != '..' ]
datanuueva3 =  datanuueva2[datanuueva2['Values'] != 0 ]
datanuueva4 =  datanuueva3.dropna()
APD = datanuueva3[datanuueva3['Region (IMF)'] == 'Asia & Pacific']
APD1 = APD.reset_index(drop=True) 
APD1['Value'] = 0
for i in range(len(APD1['Range'])):
    if APD1['Range'][i] == '[0,10000]':
        APD1['Value'][i] = 10
    elif APD1['Range'][i] == '[10001,100000]':
        APD1['Value'][i] = 200    
    elif APD1['Range'][i] == '[100001,500000]':
        APD1['Value'][i] = 1000       

APD2 = APD1[['Countries','Currencies','Value']]
APD2.columns=['source','target','value']

APD2['color'] = 0
for i in range(len(APD2['value'])):
    if APD2['value'][i] == 10:
        APD2['color'][i] = 'red'
    elif APD2['value'][i] == 200:
        APD2['color'][i] = 'blue' 
    elif APD2['value'][i] == 1000:
        APD2['color'][i] = 'yellow'
from ipywidgets import Layout
layout = Layout(width="1000",height="900")
#colormap={'CHF':'#ffcc00','JPY':'green','AUD':'blue','GBP':'red','EUR':'yellow','USD':'brown','CAD': 'purple','SEK':'gray'}
#APD2['color']=APD2['source'].apply(lambda x: colormap[x[0]])
#plt.figure(figsize=(25,16),dpi= 80) 
#plt.title('OTC Ex Turnover by Country and Currency in April 2019',fontsize=20,fontname='Monospace')
links = APD2[['source','value','color']].to_dict(orient='records')
w = SankeyWidget(links = links,width=800,height=800,margins=dict(top=0,bottom=0),layout=layout)