An extra column is added when getting items in a folder (Python)

I am creating two different lists from a data frame and then exporting those to a csv file. When I indicate what columns I want, it works fine when printing the list. But when appending to a dataframe, an extra column 'etag' is added.

for b in box_folders:
    folder_items = user_client.folder(folder_id=b).get_items(fields=('type','id','name'))  
    for item in folder_items:
            if item.type == 'folder':
                # print(f'Appending {item.name} to folder_list . . .')
                folder_list.append(item) # create a list of folders
            else :
                pass
                # if item.type == 'file'
                # print(f'Appending {item.name} to file_list . . .')
                # file_list.append(item)

# # create a dataframe for folder list
df_folders = pd.DataFrame(data = folder_list, columns=['type', 'id','etag', 'name'])

Results:

folder_list
[<Box Folder - 137845028492 (north)>,
 <Box Folder - 137845191876 (south)>,
 <Box Folder - 137175604050 (Bullitt_2009_aerial)>,
 <Box Folder - 137849896344 (30metanorth)>,
 <Box Folder - 137849654596 (30metasouth)>,
 <Box Folder - 137850072121 (DEM30FT_N)>,
 <Box Folder - 137849524642 (DEM30FT_S)>,
 <Box Folder - 137850575392 (Meta_N)>,
 <Box Folder - 1378505

df_folders
     type  id  etag  name
0    type  id  etag  name
1    type  id  etag  name
2    type  id  etag  name
3    type  id  etag  name
4    type  id  etag  name
..    ...  ..   ...   ...
227  type  id  etag  name
228  type  id  etag  name
229  type  id  etag  name
230  type  id  etag  name
231  type  id  etag  name

[232 rows x 4 columns]
file_list
[]
df_files
Empty DataFrame
Columns: []

I know it's probably simply just to write the list to csv, but what is going on here?

Comments