pandas-dev/pandas · error · ValueError

Length of indexer and values mismatch

Error message

Length of indexer and values mismatch

What it means

In the integer-key branch of __setitem__, after the index has been bounds-checked, if value is list-like (not a scalar and not a pa.Scalar) pandas raises ValueError because assigning a sequence to a single position is a length mismatch. There is no broadcasting for one slot; value must be scalar.

Solutions

1. Assign a scalar: s.iloc[3] = value[0] or pick the single element you meant to write.
2. If you intended to write multiple values, use a slice or boolean mask key of matching length.
3. Verify value is scalar with pandas.api.types.is_scalar(value) before assigning to a single index.

Example fix

// before
s = pd.Series([1, 2, 3], dtype="int64[pyarrow]")
s.iloc[0] = [99]
// after
s = pd.Series([1, 2, 3], dtype="int64[pyarrow]")
s.iloc[0] = 99

from pandas.api.types import is_scalar

def safe_scalar_setitem(arr, key, value):
    if not is_scalar(value) and not hasattr(value, "as_py"):
        raise ValueError("scalar position requires scalar value")
    arr[key] = value

from pandas.api.types import is_scalar

def value_is_scalar_like(value) -> bool:
    return is_scalar(value) or hasattr(value, "as_py")

try:
    s.iloc[i] = value
except ValueError as e:
    if "Length of indexer and values mismatch" in str(e) and is_scalar_int_key:
        s.iloc[i] = value[0]
    else:
        raise

When it happens

Trigger: s.iloc[3] = [10, 20] or arr[5] = some_list on an ArrowExtensionArray, where key is an integer but value is multi-element.

Common situations: Confusing scalar-position assignment with slice/boolean-mask assignment; passing a column-of-lists value to a single cell; off-by-one in selecting a scalar from a sequence.

Related errors

• cannot broadcast result
• Cannot divide vectors with unequal lengths
• Cannot multiply with unequal lengths
• index is out of bounds for axis 0 with size
• Lengths must match.

AI-assisted analysis of pandas-dev/pandas@3b7651241d (2026-08-11). Data as JSON: /api/errors/1d5e7b952f8e6dcf. Report an issue: GitHub.

Appendix: source

Thrown at pandas/core/arrays/arrow/array.py:2923

            ):
                data = value
            else:
                data = self._if_else(True, value, self._pa_array)

        elif is_integer(key):
            # fast path
            key = cast("int", key)
            n = len(self)
            if key < 0:
                key += n
            if not 0 <= key < n:
                raise IndexError(
                    f"index {key} is out of bounds for axis 0 with size {n}"
                )
            if isinstance(value, pa.Scalar):
                value = value.as_py()
            elif is_list_like(value):
                raise ValueError("Length of indexer and values mismatch")
            chunks = [
                *self._pa_array[:key].chunks,
                pa.array([value], type=self._pa_array.type, from_pandas=is_nan_na()),
                *self._pa_array[key + 1 :].chunks,
            ]
            data = pa.chunked_array(chunks).combine_chunks()

        elif is_bool_dtype(key):
            key = np.asarray(key, dtype=np.bool_)
            data = self._replace_with_mask(self._pa_array, key, value)

        elif is_scalar(value) or isinstance(value, pa.Scalar):
            mask = np.zeros(len(self), dtype=np.bool_)
            mask[key] = True
            data = self._if_else(mask, value, self._pa_array)

        else:
            indices = np.arange(len(self))[key]

View on GitHub (pinned to 3b7651241d)