Python test

#coding:utf-8

data_list=[
    [‘ch1’,“ce1”,“lun1”,“TU1”],
    [‘ch0’,“ce1”,“lun1”,“TU1”],
    [‘ch1’,“ce1”,“lun1”,“TU2”],
    [‘ch1’,“ce1”,“lun1”,“TU1”],
    [‘ch1’,“ce1”,“lun1”,“TU2”],
    [‘ch1’,“ce1”,“lun1”,“TU1”],
    [‘ch1’,“ce1”,“lun1”,“TU1”],
    [‘ch1’,“ce1”,“lun1”,“TU9”],
    [‘ch1’,“ce1”,“lun1”,“TU1”],
    [‘ch1’,“ce1”,“lun1”,“TU3”],
    [‘ch1’,“ce1”,“lun1”,“TU8”],
    [‘ch1’,“ce1”,“lun1”,“TU1”],
    [‘ch1’,“ce1”,“lun1”,“TU5”],
    [‘ch1’,“ce1”,“lun1”,“TU5”],
]

filer_obj={}

def probability(data):
    for item in data:
        address=item[-1]  #获取存放的地址
        tu_type=item[0]+item[1]+item[2]
        # print(tu_type,666)
        if address not in filer_obj.keys():#判断当前的tu是否存在于filter_obj的key中，如果没有给一个默认空list
            filer_obj[address]=[]
        # print(filer_obj[address],‘uuuu’)
        if tu_type not in filer_obj[address]: #前三列元素是否在分类中的list中 本意是去重
            filer_obj[address].append(tu_type)
    # print(filer_obj)
    #循环遍历生成的字典，并计算概率
    for key in filer_obj:
        num=len(filer_obj[key])  #当前tu出现的次数
        sum=100  #总数
        print("{}的概率是{}%".format(key,num/sum*100))

if name==“main”:
    probability(data_list)