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 pd
from 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 CMD
index_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 CMD
for 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('\n')