pandas-dev/pandas · error · ValueError

multi-dimensional indexing not allowed

Error message

multi-dimensional indexing not allowed

What it means

Raised in `IntervalArray.__getitem__` when the indexer yields a left/right with `np.ndim(left) > 1`. IntervalArray is 1-D; a 2-D indexer (e.g. a 2-D boolean mask, or `arr[arr_idx, col_idx]` style) is not supported (GH#30588).

Solutions

1. Flatten the indexer: use `.ravel()` on the mask or pick a single row/column first.
2. Index with a 1-D boolean array or integer positions only.
3. If you need 2-D selection, work on a DataFrame whose column is the interval, not on the bare IntervalArray.

Example fix

# before
mask = np.array([[True, False], [False, True]])
arr[mask]

# after
arr[mask.ravel()]  # 1-D indexer

import numpy as np

def to_1d_indexer(key):
    arr = np.asarray(key)
    if arr.ndim > 1:
        raise ValueError('indexer must be 1-D')
    return key

import numpy as np

def is_1d_indexer(key) -> bool:
    arr = np.asarray(key)
    return arr.ndim <= 1

try:
    sub = arr[key]
except ValueError as e:
    if 'multi-dimensional indexing not allowed' in str(e):
        sub = arr[np.asarray(key).ravel()]
    else:
        raise

When it happens

Trigger: `arr[two_dim_mask]` where the mask is shape (n, m); `arr[np.array([[0,1]])]`; passing a DataFrame as a boolean indexer.

Common situations: User mistakenly applying a 2-D mask meant for a DataFrame; chaining indexers `[row_idx, col_idx]` on a 1-D array; reshaping bugs producing 2-D index arrays.

Related errors

• Cannot mask with non-boolean array containing NA / NaN…
• Cannot modify read-only array
• closed keyword does not match dtype.closed
• invalid dtype
• left and right must have the same length

AI-assisted analysis of pandas-dev/pandas@3b7651241d (2026-08-11). Data as JSON: /api/errors/ae7e300df275526b. Report an issue: GitHub.

Appendix: source

Thrown at pandas/core/arrays/interval.py:684

    @overload
    def __getitem__(self, key: ScalarIndexer) -> IntervalOrNA: ...

    @overload
    def __getitem__(self, key: SequenceIndexer) -> Self: ...

    def __getitem__(self, key: PositionalIndexer) -> Self | IntervalOrNA:
        key = check_array_indexer(self, key)
        left = self._left[key]
        right = self._right[key]

        if not isinstance(left, (np.ndarray, ExtensionArray)):
            # scalar
            if is_scalar(left) and isna(left):
                return self._fill_value
            return Interval(left, right, self.closed)
        if np.ndim(left) > 1:
            # GH#30588 multi-dimensional indexer disallowed
            raise ValueError("multi-dimensional indexing not allowed")
        # Argument 2 to "_simple_new" of "IntervalArray" has incompatible type
        # "Union[Period, Timestamp, Timedelta, NaTType, DatetimeArray, TimedeltaArray,
        # ndarray[Any, Any]]"; expected "Union[Union[DatetimeArray, TimedeltaArray],
        # ndarray[Any, Any]]"
        result = self._simple_new(left, right, dtype=self.dtype)  # type: ignore[arg-type]
        if getitem_returns_view(self, key):
            result._readonly = self._readonly
        return result

    def __setitem__(self, key, value) -> None:
        if self._readonly:
            raise ValueError("Cannot modify read-only array")

        key = check_array_indexer(self, key)
        value_left, value_right = self._validate_setitem_value(value)

        self._left[key] = value_left
        self._right[key] = value_right

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