parameters: (self, columns=None, how="any", recursive=False)
docstring: Split rows with missing values from this SFrame. This function has the
          same functionality as :py:func:`~turicreate.SFrame.dropna`, but returns a
          tuple of two SFrames.  The first item is the expected output from
          :py:func:`~turicreate.SFrame.dropna`, and the second item contains all the
          rows filtered out by the `dropna` algorithm.
  
          Parameters
          ----------
          columns : list or str, optional
              The columns to use when looking for missing values. By default, all
              columns are used.
  
          how : {'any', 'all'}, optional
              Specifies whether a row should be dropped if at least one column
              has missing values, or if all columns have missing values.  'any' is
              default.
  
          recursive: bool
              By default is False. If this flag is set to True, then `nan` check will
              be performed on each element of a sframe cell in a recursive manner if the cell
              has a nested structure, such as dict, list.
  
  
          Returns
          -------
          out : (SFrame, SFrame)
              (SFrame with missing values removed,
               SFrame with the removed missing values)
  
          See Also
          --------
          dropna
  
          Examples
          --------
          >>> sf = turicreate.SFrame({'a': [1, None, None], 'b': ['a', 'b', None]})
          >>> good, bad = sf.dropna_split()
          >>> good
          +---+---+
          | a | b |
          +---+---+
          | 1 | a |
          +---+---+
          [1 rows x 2 columns]
  
          >>> bad
          +------+------+
          |  a   |  b   |
          +------+------+
          | None |  b   |
          | None | None |
          +------+------+
          [2 rows x 2 columns]
docstring_summary: Split rows with missing values from this SFrame. This function has the
          same functionality as :py:func:`~turicreate.SFrame.dropna`, but returns a
          tuple of two SFrames.  The first item is the expected output from
          :py:func:`~turicreate.SFrame.dropna`, and the second item contains all the
          rows filtered out by the `dropna` algorithm.
docstring_tokens: Split rows with missing values from this SFrame . This function has the same functionality as : py : func : ~turicreate . SFrame . dropna but returns a tuple of two SFrames . The first item is the expected output from : py : func : ~turicreate . SFrame . dropna and the second item contains all the rows filtered out by the dropna algorithm .
function: def dropna_split(self, columns=None, how="any", recursive=False):
          """
          Split rows with missing values from this SFrame. This function has the
          same functionality as :py:func:`~turicreate.SFrame.dropna`, but returns a
          tuple of two SFrames.  The first item is the expected output from
          :py:func:`~turicreate.SFrame.dropna`, and the second item contains all the
          rows filtered out by the `dropna` algorithm.
  
          Parameters
          ----------
          columns : list or str, optional
              The columns to use when looking for missing values. By default, all
              columns are used.
  
          how : {'any', 'all'}, optional
              Specifies whether a row should be dropped if at least one column
              has missing values, or if all columns have missing values.  'any' is
              default.
  
          recursive: bool
              By default is False. If this flag is set to True, then `nan` check will
              be performed on each element of a sframe cell in a recursive manner if the cell
              has a nested structure, such as dict, list.
  
  
          Returns
          -------
          out : (SFrame, SFrame)
              (SFrame with missing values removed,
               SFrame with the removed missing values)
  
          See Also
          --------
          dropna
  
          Examples
          --------
          >>> sf = turicreate.SFrame({'a': [1, None, None], 'b': ['a', 'b', None]})
          >>> good, bad = sf.dropna_split()
          >>> good
          +---+---+
          | a | b |
          +---+---+
          | 1 | a |
          +---+---+
          [1 rows x 2 columns]
  
          >>> bad
          +------+------+
          |  a   |  b   |
          +------+------+
          | None |  b   |
          | None | None |
          +------+------+
          [2 rows x 2 columns]
          """
  
          # If the user gives me an empty list (the indicator to use all columns)
          # NA values being dropped would not be the expected behavior. This
          # is a NOOP, so let's not bother the server
          if type(columns) is list and len(columns) == 0:
              return (SFrame(_proxy=self.__proxy__), SFrame())
  
          (columns, all_behavior) = self.__dropna_errchk(columns, how)
  
          sframe_tuple = self.__proxy__.drop_missing_values(
              columns, all_behavior, True, recursive
          )
  
          if len(sframe_tuple) != 2:
              raise RuntimeError("Did not return two SFrames!")
  
          with cython_context():
              return (SFrame(_proxy=sframe_tuple[0]), SFrame(_proxy=sframe_tuple[1]))
function_tokens: def dropna_split ( self , columns = None , how = "any" , recursive = False ) : # If the user gives me an empty list (the indicator to use all columns) # NA values being dropped would not be the expected behavior. This # is a NOOP, so let's not bother the server if type ( columns ) is list and len ( columns ) == 0 : return ( SFrame ( _proxy = self . __proxy__ ) , SFrame ( ) ) ( columns , all_behavior ) = self . __dropna_errchk ( columns , how ) sframe_tuple = self . __proxy__ . drop_missing_values ( columns , all_behavior , True , recursive ) if len ( sframe_tuple ) != 2 : raise RuntimeError ( "Did not return two SFrames!" ) with cython_context ( ) : return ( SFrame ( _proxy = sframe_tuple [ 0 ] ) , SFrame ( _proxy = sframe_tuple [ 1 ] ) )