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30 changes: 12 additions & 18 deletions pandas/core/groupby/generic.py
Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,6 @@
Tuple,
Type,
Union,
cast,
)
import warnings

Expand Down Expand Up @@ -1100,24 +1099,19 @@ def blk_func(block: "Block") -> List["Block"]:
# continue and exclude the block
raise
else:
result = cast(DataFrame, result)
assert isinstance(result, (Series, DataFrame)) # for mypy
# In the case of object dtype block, it may have been split
# in the operation. We un-split here.
result = result._consolidate()
assert isinstance(result, (Series, DataFrame)) # for mypy
assert len(result._mgr.blocks) == 1

# unwrap DataFrame to get array
if len(result._mgr.blocks) != 1:
# We've split an object block! Everything we've assumed
# about a single block input returning a single block output
# is a lie. To keep the code-path for the typical non-split case
# clean, we choose to clean up this mess later on.
assert len(locs) == result.shape[1]
for i, loc in enumerate(locs):
agg_block = result.iloc[:, [i]]._mgr.blocks[0]
agg_block.mgr_locs = [loc]
new_blocks.append(agg_block)
else:
result = result._mgr.blocks[0].values
if isinstance(result, np.ndarray) and result.ndim == 1:
result = result.reshape(1, -1)
agg_block = cast_result_block(result, block, how)
new_blocks = [agg_block]
result = result._mgr.blocks[0].values
if isinstance(result, np.ndarray) and result.ndim == 1:
result = result.reshape(1, -1)
agg_block = cast_result_block(result, block, how)
new_blocks = [agg_block]
else:
agg_block = cast_result_block(result, block, how)
new_blocks = [agg_block]
Expand Down