def eq(self, other):
        """
        Construct a Filter returning True for asset/date pairs where the output
        of ``self`` matches ``other``.
        """
        # We treat this as an error because missing_values have NaN semantics,
        # which means this would return an array of all False, which is almost
        # certainly not what the user wants.
        if other == self.missing_value:
            raise ValueError(
                "Comparison against self.missing_value ({value!r}) in"
                " {typename}.eq().\n"
                "Missing values have NaN semantics, so the "
                "requested comparison would always produce False.\n"
                "Use the isnull() method to check for missing values.".format(
                    value=other,
                    typename=(type(self).__name__),
                )
            )

        if isinstance(other, Number) != (self.dtype == int64_dtype):
            raise InvalidClassifierComparison(self, other)

        if isinstance(other, Number):
            return NumExprFilter.create(
                "x_0 == {other}".format(other=int(other)),
                binds=(self,),
            )
        else:
            return ArrayPredicate(
                term=self,
                op=operator.eq,
                opargs=(other,),
            )