Method where

pandas/core/internals/blocks.py:1687–1750

(self, other, cond)

    @final
    def where(self, other, cond) -> list[Block]:
        arr = self.values.T

        cond = extract_bool_array(cond)

        orig_other = other
        orig_cond = cond
        other = self._maybe_squeeze_arg(other)
        cond = self._maybe_squeeze_arg(cond)

        if other is lib.no_default:
            other = self.fill_value

        icond, noop = validate_putmask(arr, ~cond)
        if noop:
            # GH#44181, GH#45135
            # Avoid a) raising for Interval/PeriodDtype and b) unnecessary object upcast
            return [self.copy(deep=False)]

        try:
            res_values = arr._where(cond, other).T
        except OutOfBoundsDatetime:
            raise
        except (ValueError, TypeError):
            if self.ndim == 1 or self.shape[0] == 1:
                if isinstance(self.dtype, (IntervalDtype, StringDtype)):
                    # TestSetitemFloatIntervalWithIntIntervalValues
                    blk = self.coerce_to_target_dtype(orig_other, raise_on_upcast=False)
                    if (
                        self.ndim == 2
                        and isinstance(orig_cond, np.ndarray)
                        and orig_cond.ndim == 1
                        and not is_1d_only_ea_dtype(blk.dtype)
                    ):
                        orig_cond = orig_cond[:, None]
                    return blk.where(orig_other, orig_cond)

                elif isinstance(self, NDArrayBackedExtensionBlock):
                    # NB: not (yet) the same as
                    #  isinstance(values, NDArrayBackedExtensionArray)
                    blk = self.coerce_to_target_dtype(orig_other, raise_on_upcast=False)
                    return blk.where(orig_other, orig_cond)

                else:
                    raise

            else:
                # Same pattern we use in Block.putmask
                is_array = isinstance(orig_other, (np.ndarray, ExtensionArray))

                res_blocks = []
                for i, nb in enumerate(self._split()):
                    n = orig_other
                    if is_array:
                        # we have a different value per-column
                        n = orig_other[:, i : i + 1]

                    submask = orig_cond[:, i : i + 1]