我有以下DataFrame：

print(df)

business_id     software_id     quantity     price     inventory_level
   1234              abc           10        25.5            5
   4820              bce           40        21.9            2
   1492              abc           59        25.3            1
   1234              abc           55        11.3            0

我想创建一个字典列表，保留列名并将非键的内容（这里是“business_id”和“software_id”）存储为字典列表，使用Pandas的groupby，从而获得：

[

{
business_id: 1234,
software_id: abc,
transactions: [
      {quantity: 10, price: 25.5, inventory_level:5},
      {quantity: 55, price: 11.3, inventory_level:0},
]}
(...)
]

低效版本为：

keys_l = ["business_id", "software_id"]
keys_df = df.filter(keys_l).drop_duplicates()

chunk_l = []
for _, row in keys_df.iterrows():
    
    # --- Subset original DataFrame ---
    chunk_df = df[(df[keys_l]==row).all(axis=1)]
    
    # --- Create baseline keys with keys ---
    chunk_dict = {key: value for key, value in zip(row.index, row.values)}
    
    # --- Add bucketed data points ---
    chunk_dict["transactions"] = chunk_df.drop(keys_l, axis=1).to_dict(orient="records")
   
    # --- Append to list to create a list of dictionaries ---
    chunk_l.append(chunk_dict)

如何通过Pandas的groupby达到同样的效果？