如何从包含多列数据的 CSV 文件中合并特定列并计算各个选项出现的比例？

import pandas as pdfrom collections import Counter# 读取 CSV 文件df = pd.read_csv('test.csv', encoding='cp932')# 获取 CMD 列作为主键index_list_cmd = df['cmd'].tolist()# 计算 CMD 出现的次数idxLstCmd_cnt = Counter(list(index_list_cmd))# 去除重复的 CMDindex_list_cmd = sorted(set(index_list_cmd), key=list(index_list_cmd).index)# 计算每个 CMD 出现的次数cntLst = []for lst_i in range(len(index_list_cmd)):    cntLst.append(idxLstCmd_cnt[index_list_cmd[lst_i]])# 合并 OPT 列index_list_opt_idx = []# 删除之前保存的文件if os.path.isfile(useRateF):    os.remove(useRateF)# 遍历 CMDfor cmd_i in range(len(index_list_cmd)):    # 获得 OPT 列的 index    index_list_opt_idx = list(df['opt'][df['cmd'] == index_list_cmd[cmd_i]].index.values)    index_list_opt = []    # 遍历 OPT    for opt_i in range(len(index_list_opt_idx)):        try:            index_list_opt.append(df.loc[int(index_list_opt_idx[opt_i]), 'opt'])        except:            print(index_list_cmd[cmd_i])            print(index_list_opt_idx[opt_i])            print(opt_i)    # 列表转字符串    str_idxLstOpt = ' '.join(index_list_opt)    # 字符串转回列表    lst_idxLstOpt = str_idxLstOpt.split(' ')    # 计算 OPT 出现的比例    for tag in sorted(set(lst_idxLstOpt), key=lst_idxLstOpt.index):        with open(useRateF, 'a', encoding='utf-8_sig') as uf:            uf.writelines(str(index_list_cmd[cmd_i]) + ',' + tag + ',' + str(lst_idxLstOpt.count(tag)/cntLst[cmd_i]))            uf.writelines('')