code: def all(self, axis=0, bool_only=None, skipna=True, level=None, **kwargs):
          
          if axis is not None:
              axis = self._get_axis_number(axis)
              if bool_only and axis == 0:
                  if hasattr(self, "dtype"):
                      raise NotImplementedError(
                          "{}.{} does not implement numeric_only.".format(
                              self.__name__, "all"
                          )
                      )
                  data_for_compute = self[self.columns[self.dtypes == np.bool]]
                  return data_for_compute.all(
                      axis=axis, bool_only=False, skipna=skipna, level=level, **kwargs
                  )
              return self._reduce_dimension(
                  self._query_compiler.all(
                      axis=axis, bool_only=bool_only, skipna=skipna, level=level, **kwargs
                  )
              )
          else:
              if bool_only:
                  raise ValueError("Axis must be 0 or 1 (got {})".format(axis))
              # Reduce to a scalar if axis is None.
              result = self._reduce_dimension(
                  self._query_compiler.all(
                      axis=0, bool_only=bool_only, skipna=skipna, level=level, **kwargs
                  )
              )
              if isinstance(result, BasePandasDataset):
                  return result.all(
                      axis=axis, bool_only=bool_only, skipna=skipna, level=level, **kwargs
                  )
              return result
docs: Return whether all elements are True over requested axis
  
          Note:
              If axis=None or axis=0, this call applies df.all(axis=1)
                  to the transpose of df.