Question

我要遍历文件夹中的文件，我想基于名为key的变量合并数据集。这是到目前为止的代码。我有一个数据集可能看起来是什么样的示例/我希望最终结果看起来像什么：

dfs=[]
for f in files:   
    for name, sheet in sheets_dict.items():
        if name=="Main":
            data = sheet
            dfs.append(data)

dfs的示例：

df1 = {'key': ["A","B"], 'Answer':["yes","No"]}
df1 = pd.DataFrame(data=df1)

df2={'key': ["A","C"], 'Answer':["No","c"]}
df2 = pd.DataFrame(data=df2)

最终输出

final={'A': ["yes","No"], 'B':["No",""],'C':["","c"],'file':['df1','df2']}
final = pd.DataFrame(data=final)

这是我尝试过的方法，但是我无法使它起作用：

df_key={'key': ["A","B","C"]}
df_key = pd.DataFrame(data=df_key)

df_final=[]
for df in dfs:
    temp= pd.merge(df_key[['key']],df, on=['key'], how = 'left')
    temp_t= temp.transpose()
df_final.append(temp_t)

Answer 1

重塑和连接数据帧非常简单。但是，为了添加file值，您将需要a）将数据帧的名称包含在字符串列表中，或者b）在运行时生成新名称。

这是代码

dfs = [df1, df2] # populate dfs as needed

master_df = []
df_key = {'key': ["A","B","C"]}
df_key = pd.DataFrame(df_key) # assuming you already have this dataframe created
master_df.append(pd.Series(index=df_key.columns))

for i, df in enumerate(dfs):
    df = df.set_index('key').squeeze()
    df.loc['file'] = f'df{i+1}'
    master_df.append(df)

# or iterate the dfs alongside their file names
# for fname, df in zip(file_names, dfs):
    # df = df.set_index('key').squeeze()
    # df.loc['file'] = fname
    # master_df.append(df)

master_df = pd.concat(master_df, axis=1).T

# rearrange columns
master_df = master_df[
    master_df.columns.difference(['file']).to_list() + ['file']
]

# fill NaNs with empty string
master_df.fillna('', inplace=True)

输出

          A   B  C file
Answer  yes  No     df1
Answer   No      c  df2

在python中的for循环中合并数据帧

1 个答案: