parameters: (self, columns=None, how="any", recursive=False)
docstring: Remove missing values from an SFrame. A missing value is either ``None``
          or ``NaN``.  If ``how`` is 'any', a row will be removed if any of the
          columns in the ``columns`` parameter contains at least one missing
          value.  If ``how`` is 'all', a row will be removed if all of the columns
          in the ``columns`` parameter are missing values.
  
          If the ``columns`` parameter is not specified, the default is to
          consider all columns when searching for missing values.
  
          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 DFS manner if the cell
              has a nested structure, such as dict, list.
  
          Returns
          -------
          out : SFrame
              SFrame with missing values removed (according to the given rules).
  
          See Also
          --------
          dropna_split :  Drops missing rows from the SFrame and returns them.
  
          Examples
          --------
          Drop all missing values.
  
          >>> sf = turicreate.SFrame({'a': [1, None, None], 'b': ['a', 'b', None]})
          >>> sf.dropna()
          +---+---+
          | a | b |
          +---+---+
          | 1 | a |
          +---+---+
          [1 rows x 2 columns]
  
          Drop rows where every value is missing.
  
          >>> sf.dropna(any="all")
          +------+---+
          |  a   | b |
          +------+---+
          |  1   | a |
          | None | b |
          +------+---+
          [2 rows x 2 columns]
  
          Drop rows where column 'a' has a missing value.
  
          >>> sf.dropna('a', any="all")
          +---+---+
          | a | b |
          +---+---+
          | 1 | a |
          +---+---+
          [1 rows x 2 columns]
docstring_summary: Remove missing values from an SFrame. A missing value is either ``None``
          or ``NaN``.  If ``how`` is 'any', a row will be removed if any of the
          columns in the ``columns`` parameter contains at least one missing
          value.  If ``how`` is 'all', a row will be removed if all of the columns
          in the ``columns`` parameter are missing values.
docstring_tokens: Remove missing values from an SFrame . A missing value is either None or NaN . If how is any a row will be removed if any of the columns in the columns parameter contains at least one missing value . If how is all a row will be removed if all of the columns in the columns parameter are missing values .
function: def dropna(self, columns=None, how="any", recursive=False):
          """
          Remove missing values from an SFrame. A missing value is either ``None``
          or ``NaN``.  If ``how`` is 'any', a row will be removed if any of the
          columns in the ``columns`` parameter contains at least one missing
          value.  If ``how`` is 'all', a row will be removed if all of the columns
          in the ``columns`` parameter are missing values.
  
          If the ``columns`` parameter is not specified, the default is to
          consider all columns when searching for missing values.
  
          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 DFS manner if the cell
              has a nested structure, such as dict, list.
  
          Returns
          -------
          out : SFrame
              SFrame with missing values removed (according to the given rules).
  
          See Also
          --------
          dropna_split :  Drops missing rows from the SFrame and returns them.
  
          Examples
          --------
          Drop all missing values.
  
          >>> sf = turicreate.SFrame({'a': [1, None, None], 'b': ['a', 'b', None]})
          >>> sf.dropna()
          +---+---+
          | a | b |
          +---+---+
          | 1 | a |
          +---+---+
          [1 rows x 2 columns]
  
          Drop rows where every value is missing.
  
          >>> sf.dropna(any="all")
          +------+---+
          |  a   | b |
          +------+---+
          |  1   | a |
          | None | b |
          +------+---+
          [2 rows x 2 columns]
  
          Drop rows where column 'a' has a missing value.
  
          >>> sf.dropna('a', any="all")
          +---+---+
          | a | b |
          +---+---+
          | 1 | a |
          +---+---+
          [1 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__)
  
          (columns, all_behavior) = self.__dropna_errchk(columns, how)
  
          with cython_context():
              return SFrame(
                  _proxy=self.__proxy__.drop_missing_values(
                      columns, all_behavior, False, recursive
                  )
              )
function_tokens: def dropna ( 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__ ) ( columns , all_behavior ) = self . __dropna_errchk ( columns , how ) with cython_context ( ) : return SFrame ( _proxy = self . __proxy__ . drop_missing_values ( columns , all_behavior , False , recursive ) )