pandas-dev/pandas · error · ValueError

Length of indexer and values mismatch

Error message

Length of indexer and values mismatch

What it means

Raised on the integer-key setitem path when the value is list-like. Assigning to a single scalar position requires a scalar value; passing a sequence is a shape mismatch pandas rejects immediately.

Source

Thrown at pandas/core/arrays/arrow/array.py:2898

            ):
                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 71959b8cb9)

Solutions

1. Pass a scalar: `arr[k] = scalar`.
2. If you intended to assign multiple, use a matching-length index array: `arr[[k1, k2, k3]] = values`.
3. Extract the scalar element from the sequence before assignment.

Example fix

// before
arr = pd.array([1, 2, 3], dtype="int64[pyarrow]")
arr[0] = [10, 20]

// after
arr[[0, 1]] = [10, 20]

from pandas.api.types import is_scalar

def coerce_scalar_value(arr, k, value):
    if not is_scalar(value):
        raise ValueError("single integer index requires scalar value")
    return value

def is_scalar_value(value) -> bool:
    from pandas.api.types import is_scalar
    return bool(is_scalar(value))

try:
    arr[k] = value
except ValueError as e:
    if "Length of indexer and values mismatch" in str(e) and isinstance(value, (list, tuple)):
        arr[[k] * len(value)] = value
    else:
        raise

When it happens

Trigger: Doing `arr[k] = [a, b, c]` (k integer) — assigning a list/array to a single positional slot of an ArrowExtensionArray.

Common situations: Loop bugs that pass a row of values to a single index, or confusing scalar vs array assignment semantics.

Related errors

• index {key} is out of bounds for axis 0 with size {n}
• cannot do a non-empty take
• out of bounds value in 'indices'.
• Function did not transform
• putmask: mask and data must be the same size

AI-assisted analysis of pandas-dev/pandas@71959b8cb9 (2026-08-07). Data as JSON: /api/errors/1d5e7b952f8e6dcf. Report an issue: GitHub.