如何在 for 循环 python 中将 append 子集数据帧到另一个空数据帧

Question

I'm having one empty data-frame and a list of columns in list1. I want append the subset data-frame to empty in a for loop.

df
        
    A1 A2  B1   B2
0   1  11  21   31
1   2  12  22   32 
2   3  13  23   33
3   4  14  24   34


empty_df = pd.DataFrame()

listl = [['A1','A2'],['B1','B2']]

for columns in list1:
    empty_df = empty_df.append(df[columns])

Here when I executed above code I'm getting shape(16X4), where I should get shape(16X1) Which should look like.

df

0  1 11
1  2 12
2  3 13
3  4 14
4  21 31
5  22 32
6  23 33
7  24 34

Also is it possible to add another column which describes previous column names like...

df

0  1 11 A
1  2 12 A
2  3 13 A
3  4 14 A
4  21 31 B
5  22 32 B
6  23 33 B
7  24 34 B

Answer 1

listl = [['A1','A2'],['B1','B2']]
names = ["A", "B"]                   # or [a_list[0][0] for a_list in listl]

result = pd.DataFrame()

for name, cols in zip(names, listl):
    df_to_concat = df.loc[:, cols]
    df_to_concat.columns = [f"col{j}" for j in range(len(cols))]
    df_to_concat["name"] = name
    result = pd.concat([result, df_to_concat]).reset_index(drop=True)

First we get the df to concatanate, then rename its columns to ease the concatanatetion process, then put a name column to it to signal where it came from and lastly concatanate with what we already have in result (and reset the index to have a 0..N index).

>>> result

   col0  col1 name
0     1    11    A
1     2    12    A
2     3    13    A
3     4    14    A
4    21    31    B
5    22    32    B
6    23    33    B
7    24    34    B