我有以下dataframe：

index   name     path
0       Dina     "gs://my_bucket/folder1/img1.png"
1       Dina     "gs://my_bucket/folder1/img2.png"
2       Lane     "gs://my_bucket/folder1/img3.png"
3       Bari     "gs://my_bucket/folder1/img4.png"
4       Andrew   "gs://my_bucket/folder1/img5.png"
5       Andrew   "gs://my_bucket/folder1/img6.png"
6       Andrew   "gs://my_bucket/folder1/img7.png"
7       Beti     "gs://my_bucket/folder1/img7.png"
8       Ladin    "gs://my_bucket/folder1/img5.png"
...

我想得到新的dataframe这将有唯一的名称只出现一次，路径列将与匹配的路径列表。输出应该如下所示：

index   name     path
0       Dina     ["gs://my_bucket/folder1/img1.png","gs://my_bucket/folder1/img2.png"]
1       Lane     ["gs://my_bucket/folder1/img3.png"]
2       Bari     ["gs://my_bucket/folder1/img4.png"]
3       Andrew   ["gs://my_bucket/folder1/img5.png","gs://my_bucket/folder1/img6.png","gs://my_bucket/folder1/img7.png"]
4       Beti     ["gs://my_bucket/folder1/img7.png"]
5       Ladin    ["gs://my_bucket/folder1/img5.png"]
...

结果的行数应等于 Dataframe 中的唯一名称。目前我正在使用我用chatgpt做的东西，但它使用了我不明白为什么要使用它的函数，而且它重复了行的名称，所以如果我知道我假设有842个唯一的名称，我得到992个。
这是chatGPT解决方案：

# Define a custom aggregation function to combine links as a list
def combine_links(links):
    return list(set(links))  # Convert links to a list and remove duplicates

# Group the GeoDataFrame by 'name' and 'dili' and aggregate the 'link' column
result = df.groupby(['name'))['path'].agg(combine_links).reset_index()

我的目标是找到一个解决方案，最终给我正确的行数，这是唯一名称的数量。