df = pdread_csv2023_2_20No22023_2_20_19csvencoding = utf-8df = dfiloc118df_tumor = dfdfname == tumordf_peritumor = dfdfname == peritumor dfname = dfname + dfpropertytumor_dict = peritumor_dict = for

可以使用Python的os模块来遍历文件夹中的所有文件。具体步骤如下：

1. 导入os模块：import os

2. 指定文件夹路径：folder_path = './2023_2_20No2/'

3. 遍历文件夹中的所有文件：for filename in os.listdir(folder_path):

4. 判断文件是否为csv文件：if filename.endswith('.csv'):

5. 读取csv文件：df = pd.read_csv(os.path.join(folder_path, filename), encoding='utf-8')

6. 对读取的数据进行处理。

完整代码示例：

import os
import pandas as pd

folder_path = './2023_2_20No2/'
tumor_dict = {}
peritumor_dict = {}

for filename in os.listdir(folder_path):
    if filename.endswith('.csv'):
        df = pd.read_csv(os.path.join(folder_path, filename), encoding='utf-8')
        df = df.iloc[:, 1:18]
        df_tumor = df[df['name'] == 'tumor']
        df_peritumor = df[df['name'] == 'peritumor']
        df['name'] = df['name'] + df['property']
        for name in ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H']:
            df_tumor_name = df_tumor[df_tumor['property'] == name]
            df_peritumor_name = df_peritumor[df_peritumor['property'] == name]
            tumor_dict[name] = df_tumor_name
            peritumor_dict[name] = df_peritumor_name

该代码将遍历文件夹中的所有csv文件，并将它们读取为DataFrame对象。然后，对每个DataFrame对象进行处理，最终得到两个字典tumor_dict和peritumor_dict，它们分别包含了肿瘤和周围组织的各个部位的数据