ValueError: несовместимый индексатор с серией в pandas DataFrame ⇐ Python

[Anonymous]

• python: 3.11
• pandas: 2.2.2

Мне нужно чтобы присвоить значение dict 4-й строке в df:
df = pd.DataFrame({'agg': [None] * 5})
df['agg'] = df['agg'].astype(object)
df.loc[3, 'agg'] = {'mm': 4}

Выдает ошибку:
Traceback (most recent call last):
File "/home/sirjay/python/ethereum/lib/analyse_30m.py", line 1898, in
df.loc[3, 'agg'] = {'mm': 4}
~~~~~~^^^^^^^^^^
File "/home/sirjay/miniconda3/envs/eth/lib/python3.11/site-packages/pandas/core/indexing.py", line 911, in __setitem__
iloc._setitem_with_indexer(indexer, value, self.name)
File "/home/sirjay/miniconda3/envs/eth/lib/python3.11/site-packages/pandas/core/indexing.py", line 1944, in _setitem_with_indexer
self._setitem_single_block(indexer, value, name)
File "/home/sirjay/miniconda3/envs/eth/lib/python3.11/site-packages/pandas/core/indexing.py", line 2189, in _setitem_single_block
value = self._align_series(indexer, Series(value))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/sirjay/miniconda3/envs/eth/lib/python3.11/site-packages/pandas/core/indexing.py", line 2455, in _align_series
raise ValueError("Incompatible indexer with Series")
ValueError: Incompatible indexer with Series

Как исправить? Эта опция df['agg'].loc[3] = {'mm': 4 работает, но с предупреждением:
Use `df.loc[row_indexer, "col"] = values` instead, to perform the assignment in a single step and ensure this keeps updating the original `df`.

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/s ... sus-a-copy


Подробнее здесь: https://stackoverflow.com/questions/791 ... -dataframe