Python 将数据帧转换为对象字典

需要按文件编号对行进行分组，文件编号将用作字典键，并将操作ID和操作注释作为对象

数据帧

**File_Number**   **Action_ID**    **Action_Note**
       0              12          Call Josh
       1              15          Text Emily
       1              16          Email Guy
       2              19          Visit Hannah
       2              20          Call Ryan

预期产出

{
0: [Action_ID: 12, Action_Note: Call Josh ],
1: [Action_ID: 15, Action_Note: Text Emily], [Action_ID: 16, Action_Note: Email Guy],
2: [Action_ID: 19, Action_Note: Visit Hannah], [Action_ID: 20, Action_Note: Call Ryan],
}

---

您可以执行两次以下操作：

(df.drop(['File_Number'], axis=1)
   .groupby(df['File_Number']).apply(lambda x: x.to_dict('records'))
   .to_dict()
)

输出：

{0: [{'Action_ID': 12, 'Action_Note': 'Call Josh'}],
 1: [{'Action_ID': 15, 'Action_Note': 'Text Emily'},
  {'Action_ID': 16, 'Action_Note': 'Email Guy'}],
 2: [{'Action_ID': 19, 'Action_Note': 'Visit Hannah'},
  {'Action_ID': 20, 'Action_Note': 'Call Ryan'}]}

---

您可以执行两次以下操作：

(df.drop(['File_Number'], axis=1)
   .groupby(df['File_Number']).apply(lambda x: x.to_dict('records'))
   .to_dict()
)

输出：

{0: [{'Action_ID': 12, 'Action_Note': 'Call Josh'}],
 1: [{'Action_ID': 15, 'Action_Note': 'Text Emily'},
  {'Action_ID': 16, 'Action_Note': 'Email Guy'}],
 2: [{'Action_ID': 19, 'Action_Note': 'Visit Hannah'},
  {'Action_ID': 20, 'Action_Note': 'Call Ryan'}]}

---

正是我需要的。非常感谢你！正是我需要的。非常感谢你！