In [9]: imp_mean.transform(X)
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
File /path/to/modules/packages/conda/4.6.14/envs/myenv/lib/python3.10/site-packages/pandas/core/indexes/base.py:3803, in Index.get_loc(self, key, method, tolerance)
   3802 try:
-> 3803     return self._engine.get_loc(casted_key)
   3804 except KeyError as err:

File /path/to/modules/packages/conda/4.6.14/envs/myenv/lib/python3.10/site-packages/pandas/_libs/index.pyx:138, in pandas._libs.index.IndexEngine.get_loc()

File /path/to/modules/packages/conda/4.6.14/envs/myenv/lib/python3.10/site-packages/pandas/_libs/index.pyx:144, in pandas._libs.index.IndexEngine.get_loc()

TypeError: '(slice(None, None, None), array([1, 2]))' is an invalid key

During handling of the above exception, another exception occurred:

InvalidIndexError                         Traceback (most recent call last)
Cell In [9], line 1
----> 1 imp_mean.transform(X).set_output(transform= None)

File ~/scikit-learn/sklearn/utils/_set_output.py:137, in _wrap_method_output.<locals>.wrapped(self, X, *args, **kwargs)
    135 @wraps(f)
    136 def wrapped(self, X, *args, **kwargs):
--> 137     data_to_wrap = f(self, X, *args, **kwargs)
    138     if isinstance(data_to_wrap, tuple):
    139         # only wrap the first output for cross decomposition
    140         return (
    141             _wrap_data_with_container(method, data_to_wrap[0], X, self),
    142             *data_to_wrap[1:],
    143         )

File ~/scikit-learn/sklearn/impute/_iterative.py:755, in IterativeImputer.transform(self, X)
    753 start_t = time()
    754 for it, estimator_triplet in enumerate(self.imputation_sequence_):
--> 755     Xt, _ = self._impute_one_feature(
    756         Xt,
    757         mask_missing_values,
    758         estimator_triplet.feat_idx,
    759         estimator_triplet.neighbor_feat_idx,
    760         estimator=estimator_triplet.estimator,
    761         fit_mode=False,
    762     )
    763     if not (it + 1) % imputations_per_round:
    764         if self.verbose > 1:

File ~/scikit-learn/sklearn/impute/_iterative.py:360, in IterativeImputer._impute_one_feature(self, X_filled, mask_missing_values, feat_idx, neighbor_feat_idx, estimator, fit_mode)
    357     return X_filled, estimator
    359 # get posterior samples if there is at least one missing value
--> 360 X_test = _safe_indexing(X_filled[:, neighbor_feat_idx], missing_row_mask)
    361 if self.sample_posterior:
    362     mus, sigmas = estimator.predict(X_test, return_std=True)

File /path/to/modules/packages/conda/4.6.14/envs/myenv/lib/python3.10/site-packages/pandas/core/frame.py:3804, in DataFrame.__getitem__(self, key)
   3802 if self.columns.nlevels > 1:
   3803     return self._getitem_multilevel(key)
-> 3804 indexer = self.columns.get_loc(key)
   3805 if is_integer(indexer):
   3806     indexer = [indexer]

File /path/to/modules/packages/conda/4.6.14/envs/myenv/lib/python3.10/site-packages/pandas/core/indexes/base.py:3810, in Index.get_loc(self, key, method, tolerance)
   3805         raise KeyError(key) from err
   3806     except TypeError:
   3807         # If we have a listlike key, _check_indexing_error will raise
   3808         #  InvalidIndexError. Otherwise we fall through and re-raise
   3809         #  the TypeError.
-> 3810         self._check_indexing_error(key)
   3811         raise
   3813 # GH#42269

File /path/to/modules/packages/conda/4.6.14/envs/myenv/lib/python3.10/site-packages/pandas/core/indexes/base.py:5966, in Index._check_indexing_error(self, key)
   5962 def _check_indexing_error(self, key):
   5963     if not is_scalar(key):
   5964         # if key is not a scalar, directly raise an error (the code below
   5965         # would convert to numpy arrays and raise later any way) - GH29926
-> 5966         raise InvalidIndexError(key)

InvalidIndexError: (slice(None, None, None), array([1, 2]))