text: Title: KeyError when indexing into Series after calling `to_series` on Scalar
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  **Describe the issue**:
  
  **Minimal Complete Verifiable Example**:
  
  ```python
  In [1]: import dask.dataframe as dd
  
  In [2]: import pandas as pd
  
  In [3]: data = {"a": [1, 3, 2]}
  
  In [4]: df = dd.from_pandas(pd.DataFrame(data), npartitions=2)
  
  In [5]: df['a'].sum().to_series().fillna(0)[0].compute()
  ---------------------------------------------------------------------------
  KeyError                                  Traceback (most recent call last)
  File ~/polars-api-compat-dev/.venv/lib/python3.12/site-packages/pandas/core/indexes/base.py:3805, in Index.get_loc(self, key)
     3804 try:
  -> 3805     return self._engine.get_loc(casted_key)
     3806 except KeyError as err:
  
  File index.pyx:167, in pandas._libs.index.IndexEngine.get_loc()
  
  File index.pyx:196, in pandas._libs.index.IndexEngine.get_loc()
  
  File pandas/_libs/hashtable_class_helper.pxi:2606, in pandas._libs.hashtable.Int64HashTable.get_item()
  
  File pandas/_libs/hashtable_class_helper.pxi:2630, in pandas._libs.hashtable.Int64HashTable.get_item()
  
  KeyError: 0
  
  The above exception was the direct cause of the following exception:
  
  KeyError                                  Traceback (most recent call last)
  Cell In[5], line 1
  ----> 1 df['a'].sum().to_series().fillna(0)[0].compute()
  
  File ~/polars-api-compat-dev/.venv/lib/python3.12/site-packages/dask/dataframe/dask_expr/_collection.py:489, in FrameBase.compute(self, fuse, concatenate, **kwargs)
      487     out = out.repartition(npartitions=1)
      488 out = out.optimize(fuse=fuse)
  --> 489 return DaskMethodsMixin.compute(out, **kwargs)
  
  File ~/polars-api-compat-dev/.venv/lib/python3.12/site-packages/dask/base.py:374, in DaskMethodsMixin.compute(self, **kwargs)
      350 def compute(self, **kwargs):
      351     """Compute this dask collection
      352 
      353     This turns a lazy Dask collection into its in-memory equivalent.
     (...)
      372     dask.compute
      373     """
  --> 374     (result,) = compute(self, traverse=False, **kwargs)
      375     return result
  
  File ~/polars-api-compat-dev/.venv/lib/python3.12/site-packages/dask/base.py:662, in compute(traverse, optimize_graph, scheduler, get, *args, **kwargs)
      659     postcomputes.append(x.__dask_postcompute__())
      661 with shorten_traceback():
  --> 662     results = schedule(dsk, keys, **kwargs)
      664 return repack([f(r, *a) for r, (f, a) in zip(results, postcomputes)])
  
  File ~/polars-api-compat-dev/.venv/lib/python3.12/site-packages/pandas/core/indexes/base.py:3812, in Index.get_loc(self, key)
     3807     if isinstance(casted_key, slice) or (
     3808         isinstance(casted_key, abc.Iterable)
     3809         and any(isinstance(x, slice) for x in casted_key)
     3810     ):
     3811         raise InvalidIndexError(key)
  -> 3812     raise KeyError(key) from err
     3813 except TypeError:
     3814     # If we have a listlike key, _check_indexing_error will raise
     3815     #  InvalidIndexError. Otherwise we fall through and re-raise
     3816     #  the TypeError.
     3817     self._check_indexing_error(key)
  
  KeyError: 0
  ```
  If I `compute` before the `[0]`, then I get:
  ```
  In [6]: df['a'].sum().to_series().fillna(0).compute()
  Out[6]: 
  0    6
  dtype: int64
  ```
  so I'd have expected the `[0]` to work
  
  **Anything else we need to know?**:
  spotted in Narwhals
  
  **Environment**:
  
  - Dask version: 2025.1.0
  - Python version: 3.12
  - Operating System: linux
  - Install method (conda, pip, source): pip
  