code: def update(self, other):
          
          other = other.reindex_like(self)
          mask = notna(other)
  
          self._data = self._data.putmask(mask=mask, new=other, inplace=True)
          self._maybe_update_cacher()
docs: Modify Series in place using non-NA values from passed
          Series. Aligns on index.
  
          Parameters
          ----------
          other : Series
  
          Examples
          --------
          >>> s = pd.Series([1, 2, 3])
          >>> s.update(pd.Series([4, 5, 6]))
          >>> s
          0    4
          1    5
          2    6
          dtype: int64
  
          >>> s = pd.Series(['a', 'b', 'c'])
          >>> s.update(pd.Series(['d', 'e'], index=[0, 2]))
          >>> s
          0    d
          1    b
          2    e
          dtype: object
  
          >>> s = pd.Series([1, 2, 3])
          >>> s.update(pd.Series([4, 5, 6, 7, 8]))
          >>> s
          0    4
          1    5
          2    6
          dtype: int64
  
          If ``other`` contains NaNs the corresponding values are not updated
          in the original Series.
  
          >>> s = pd.Series([1, 2, 3])
          >>> s.update(pd.Series([4, np.nan, 6]))
          >>> s
          0    4
          1    2
          2    6
          dtype: int64