code: def appendBias(data):
          
          vec = _convert_to_vector(data)
          if isinstance(vec, SparseVector):
              newIndices = np.append(vec.indices, len(vec))
              newValues = np.append(vec.values, 1.0)
              return SparseVector(len(vec) + 1, newIndices, newValues)
          else:
              return _convert_to_vector(np.append(vec.toArray(), 1.0))
docs: Returns a new vector with `1.0` (bias) appended to
          the end of the input vector.