从Python目录中的多个CSV文件中提取特定列

我的目录中大约有200个CSV文件，其中包含不同的列，但有些文件中有我要提取的数据。我要拉的一列称为“ Programme”（行的顺序不同，但名称相同），另一列包含“ would荐”（并非所有措辞都相同，但它们都将包含该措辞）。最终，我想为每个CSV提取这些列下的所有行，并将它们附加到仅包含这两列的数据框中。我尝试过仅使用一个CSV来完成此操作，但无法使其正常工作。这是我尝试过的：

import pandas as pd
from io import StringIO

df =  pd.read_csv("test.csv")

dfout = pd.DataFrame(columns=['Programme', 'Recommends'])

for file in [df]:
    dfn = pd.read_csv(file)
    matching = [s for s in dfn.columns if "would recommend" in s]
    if matching:
        dfn = dfn.rename(columns={matching[0]:'Recommends'})
        dfout = pd.concat([dfout, dfn], join="inner")

print(dfout)

我收到以下错误消息，因此我认为这是一个格式问题（它不喜欢熊猫df？）：ValueError（msg.format（_type = type（filepath_or_buffer）））ValueError：无效的文件路径或缓冲区对象类型： <class'pandas.core.frame.DataFrame'>

当我尝试这个：

csv1 = StringIO("""Programme,"Overall, I am satisfied with the quality of the programme",I would recommend the company to a friend or colleague,Please comment on any positive aspects of your experience of this programme
Nursing,4,4,IMAGE
Nursing,1,3,very good
Nursing,4,5,I enjoyed studying tis programme""")

csv2 = StringIO("""Programme,I would recommend the company to a friend,The programme was well organised and running smoothly,It is clear how students' feedback on the programme has been acted on
IT,4,2,4
IT,5,5,5
IT,5,4,5""")

dfout = pd.DataFrame(columns=['Programme', 'Recommends'])

for file in [csv1,csv2]:
    dfn = pd.read_csv(file)
    matching = [s for s in dfn.columns if "would recommend" in s]
    if matching:
        dfn = dfn.rename(columns={matching[0]:'Recommends'})
        dfout = pd.concat([dfout, dfn], join="inner")

print(dfout)

这工作正常，但我需要读入CSV文件。有任何想法吗？

以上示例的预期输出：