按线连接箱线图中的中值

Question

我试着用一条线连接箱线图的中值，但是我没能做出来，我包括了我的图和我的代码。 我看过其他帖子，但使用了熊猫模块，但我以前没有使用过

为此： 将绿线与另一条绿线连接，将黄线与另一条黄线连接

import sys
import csv
import numpy as np
import matplotlib.pyplot as plt
from collections import namedtuple
from itertools import combinations
from random import randrange, choice
import numpy as np
from functools import cmp_to_key

point = namedtuple('point','x y z')#crea la tupla
fieldnames=["node_code","node_type","wlan_code","destination_id","x(m)","y(m)","z(m)","primary_channel","min_channel_allowed","max_channel_allowed","cw","cw_stage","tpc_min(dBm)","tpc_default(dBm)","tpc_max(dBm)","cca_min(dBm)","cca_default(dBm)","cca_max(dBm)","tx_antenna_gain","rx_antenna_gain","channel_bonding_model","modulation_default","central_freq (GHz)","lambda","ieee_protocol","traffic_load(pkts/s)"]#encabezados
#######FUNCIONES QUE EJECUTA EL PROGRAMA
def calcular_distancia(p1,p2):#FUNCION DE DISTANCIA
    return np.sqrt((p1.x-p2.x)**2+(p1.y-p2.y)**2+(p1.z-p2.z)**2)
def set_box_color1(bp1, color):
    plt.setp(bp1['boxes'], color=color)
    plt.setp(bp1['whiskers'], color=color)
    plt.setp(bp1['caps'], color=color)
    plt.setp(bp1['medians'], color='lime')
    plt.setp(bp1['fliers'], color=color)
def set_box_color2(bp2, color):
    plt.setp(bp2['boxes'], color=color)
    plt.setp(bp2['whiskers'], color=color)
    plt.setp(bp2['caps'], color=color)
    plt.setp(bp2['medians'], color='yellow')
    plt.setp(bp2['fliers'], color=color)
########################################################################
def main():
    sample1=[]
    sample2=[]
    posiciones=[]
    for arch_coord,arch_result in [("nodos_escn300_topologia1.csv","resultados_escn300_100_topologia1_v1_v2.csv"),("nodos_escn300_topologia2.csv","resultados_escn300_100_topologia2_v1_v2.csv")]:
        main = {} #diccionario QUE GUARDA TUPLA CON (ORIGEN/DESTINO/DISTANCIA/CANAL)
        with open(arch_coord,'r') as inputfile:
             reader = csv.DictReader(inputfile,delimiter=";",fieldnames=fieldnames )
             for row in reader:
                 if row['node_type']=='0':
                    main.update({row['wlan_code']:{'point':point(x=float(row['x(m)']),y=float(row['y(m)']), z= float(row['z(m)'])),'channel':row['primary_channel']}})

        temp=[]
        for item in combinations(main,2):
            d = calcular_distancia(main[item[0]]['point'],main[item[1]]['point'])
            temp.append(d)
            #print(item,d)

        posiciones.append(np.mean(temp))
        print(np.mean(temp))
        #print(posiciones)
        sample1_1 = []
        sample1_2 = []

        with open(arch_result,'r') as fhan:
            reader = csv.reader(fhan,delimiter=',')
            for row in reader:
                sample1_1.append(float(row[0]))
                sample1_2.append(float(row[1]))

            sample1.append(sample1_1)
            sample2.append(sample1_2)
    ax = plt.gca()
    bp1 = plt.boxplot(sample1,positions=np.array(posiciones)*1.0-0.4, widths = 0.6)
    set_box_color1(bp1,'red')
    bp2 = plt.boxplot(sample2,positions=np.array(posiciones)*1.0+0.4, widths = 0.6)
    set_box_color2(bp2,'blue')    
    plt.plot([], c='red', label='Brute Force')
    plt.plot([], c='blue', label='Enhanced')
    plt.legend()
    plt.xticks(rotation='vertical')
    #plt.xticks(range(1,len(posiciones)*1,15),posiciones,rotation='vertical')
    plt.xlim(100,215)
    plt.title("Grafica de Escenario 300(100 topologias)") 
    plt.xlabel("Distancia promedio")
    #plt.ylabel("Throughput")
    plt.grid(True)
    plt.show()

我感谢你能为我提供的一切帮助

Answer 1

尝试添加以下代码：

import seaborn as sns
# you will have to find a work around with group by which will relate with your data
sns.pointplot(x='group', y='value', data=df.groupby('group', as_index=False).median(), ax=ax)