code: def fromNumpy(cls, data):
          
          assert np is not None
          if isinstance(data, np.ndarray):
              index = []
              if len(data.shape) == 1:
                  columns = [('value', data.tolist())]
              elif len(data.shape) == 2:
                  columns = [
                      ('c{}'.format(i), col)
                      for i, col in enumerate(zip(*data.tolist()))
                  ]
              else:
                  raise TypeError
          else:
              raise TypeError
          return cls(index=index, columns=columns)
docs: Create a :class:`~amplpy.DataFrame` from a numpy array or matrix.