[Python知识库]python运行程序报错：‘＞‘ not supported between instances of ‘NoneType‘ and ‘int‘

```python

import openpyxl
import numpy as np
import matplotlib.pyplot as plt
import math
import random
import sympy
import os
 
def array_frequent(lst):
    from collections import Counter
    HF = Counter(lst).most_common(1)
    return HF[0][0]
 
#数据打开文件路径
Tain_set = openpyxl.load_workbook(os.path.abspath('C:\\Users\\admin\\Desktop\\data.xlsx'))


#输入表格名file_data
# 要读该列的行数从1到row_end
def ReadInCol(file_data,ClassNum,row_end):
    BoyData = []
    GirData = []
    ClassNum = ClassNum+1
    for i in range(2, row_end):
            Gender  = file_data.cell(i,2).value   # 读性别
            if Gender :
                BoyData.append(file_data.cell(i,ClassNum).value)
            else:
                GirData.append(file_data.cell(i,ClassNum).value)
    return BoyData,GirData
 
#男女50米跑直方图显示
# sheet 数据字典
def Meter50_HistShow(sheet):
    # 1性别 2籍贯 3身高 4体重     5鞋码 6(50米成绩) 7肺活量     8喜欢颜色 9喜欢运动 10喜欢文学
    Boy50, Gir50 = ReadInCol(Tain_sheet,7,350)  # 提取男女50米成绩数组
    Boy50_Max = max(Boy50)
    Boy50_Min = min(Boy50)
    Gir50_Max = max(Gir50)
    Gir50_Min = min(Gir50)
    DataMax = max(Boy50_Max, Gir50_Max)
    DataMin = min(Boy50_Min, Gir50_Min)
    X_Show = np.linspace(DataMin, DataMax, round(round(DataMax - DataMin) * 2))
    plt.hist(Boy50, X_Show, density=1, color='yellowgreen', histtype='bar', alpha=0.5, edgecolor='white', linewidth=4)
    plt.hist(Gir50, X_Show, density=1, color='pink', histtype='bar', alpha=0.5, edgecolor='white', linewidth=4)
    plt.xlabel('X_hight')
    plt.ylabel('Y_Frequency')
    plt.title('50MeterTime DistributionHist')
    fig = plt.gcf()
    plt.show()
    


#训练数据读取#（4）
Tain_sheet = Tain_set["Sheet1"]
#（1）男女50米跑直方图显示
Meter50_HistShow(Tain_sheet)

```
报错显示'>' not supported between instances of 'NoneType' and 'int'

一直报错，刚开始通过加print(max(Boy50))测试，发现还是报错。以为是max()问题，然后单独写了函数测试

list1 = [1,2,3,4,5,3,2,0]
print(type(list1))
print(max(list1))

发现执行没有问题

然后才想到'>'的问题，考虑到可能是数据缺失，写一部分进行处理，发现果然是这样。

用list.index(None)查找缺失值的位置，例子如下：

list1 = [1,None,3,4,5,3,2,0]
list2 = list1[1:4]
print(type(list2))
print(list1.index(None))   

然后专门写了行处理数据缺失的命令

 if file_data.cell(i,ClassNum).value != None:

然后正常运行