嵌套列表的计数问题; matplotlib如何平铺图像

Question

将IBM收盘价序列分为5个长度一段（共400段），利用可见图算法将生成每段图，并统计400段中重复出现次数最多的一个图。

import networkx as nx 
import pandas as pd
import numpy as np
import networkx as nx 
import matplotlib.pyplot as plt
djitt = pd.read_csv('DJITT.csv')

pd.options.display.max_columns = None
ibm = djitt["IBM"].to_list()
ibm = ibm[:2000]
ibm_sliced = [ibm[i:i + 5] for i in range(0, len(ibm), 5)]

def vg(series):
    temp=np.zeros(shape=(100,2))
    n=len(series)
    for i in range(2,n+1):
        temp[i-1,0]=i-1
        temp[i-1,1]=i
    nnn1=n-1     
    for i in range(1,n-1):
        for j in range(i+2,n+1):
            poke=1
            slope0=float((series[j-1]-series[i-1]))/(j-i)
            for k in range(i+1,j): 
                if float((series[k-1]-series[i-1]))/(k-i)<slope0:
                    poke=poke*1
                else:
                    poke=poke*0
            if poke==1:
                nnn1=nnn1+1
                temp[nnn1,0]=i
                temp[nnn1,1]=j
    return temp

for series in ibm_sliced:
    Re=vg(series)
    Re=pd.DataFrame(Re)
    Re=Re.loc[~(Re==0).all(axis=1), :]  # 删了全为0的行
    g1.append(Re)
    Re=np.array(Re)
    gg1=list(Re)
    G=nx.Graph(gg1)
    nx.draw_networkx(G,node_size = 400)

首先，画出来的图像都堆在一起，要如何将400张图分成比如10x40的分布状；
其次，要如何统计相同结果图出现的次数呢？