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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _try_cast(self, result, obj, numeric_only=False):
 """ Try to cast the result to our obj original type, we may have roundtripped through object in the mean-time. If numeric_only is True, then only try to cast numerics and not datetimelikes. """

        if obj.ndim > 1:
            dtype = obj._values.dtype
        else:
            dtype = obj.dtype

        if not is_scalar(result):
            if is_datetime64tz_dtype(dtype):
                # GH 23683
                # Prior results _may_ have been generated in UTC.
                # Ensure we localize to UTC first before converting
                # to the target timezone
                try:
                    result = obj._values._from_sequence(
                        result, dtype='datetime64[ns, UTC]'
                    )
                    result = result.astype(dtype)
                except TypeError:
                    # _try_cast was called at a point where the result
                    # was already tz-aware
                    pass
            elif is_extension_array_dtype(dtype):
                # The function can return something of any type, so check
                # if the type is compatible with the calling EA.
                try:
                    result = obj._values._from_sequence(result, dtype=dtype)
                except Exception:
                    # https://github.com/pandas-dev/pandas/issues/22850
                    # pandas has no control over what 3rd-party ExtensionArrays
                    # do in _values_from_sequence. We still want ops to work
                    # though, so we catch any regular Exception.
                    pass
            elif numeric_only and is_numeric_dtype(dtype) or not numeric_only:
                result = maybe_downcast_to_dtype(result, dtype)

        return result