parameters: (self)
docstring: Whether all the columns in a DataFrame have the same type.
  
          Returns
          -------
          bool
  
          Examples
          --------
          >>> DataFrame({"A": [1, 2], "B": [3, 4]})._is_homogeneous_type
          True
          >>> DataFrame({"A": [1, 2], "B": [3.0, 4.0]})._is_homogeneous_type
          False
  
          Items with the same type but different sizes are considered
          different types.
  
          >>> DataFrame({
          ...    "A": np.array([1, 2], dtype=np.int32),
          ...    "B": np.array([1, 2], dtype=np.int64)})._is_homogeneous_type
          False
docstring_summary: Whether all the columns in a DataFrame have the same type.
docstring_tokens: Whether all the columns in a DataFrame have the same type .
function: def _is_homogeneous_type(self):
          """
          Whether all the columns in a DataFrame have the same type.
  
          Returns
          -------
          bool
  
          Examples
          --------
          >>> DataFrame({"A": [1, 2], "B": [3, 4]})._is_homogeneous_type
          True
          >>> DataFrame({"A": [1, 2], "B": [3.0, 4.0]})._is_homogeneous_type
          False
  
          Items with the same type but different sizes are considered
          different types.
  
          >>> DataFrame({
          ...    "A": np.array([1, 2], dtype=np.int32),
          ...    "B": np.array([1, 2], dtype=np.int64)})._is_homogeneous_type
          False
          """
          if self._data.any_extension_types:
              return len({block.dtype for block in self._data.blocks}) == 1
          else:
              return not self._data.is_mixed_type
function_tokens: def _is_homogeneous_type ( self ) : if self . _data . any_extension_types : return len ( { block . dtype for block in self . _data . blocks } ) == 1 else : return not self . _data . is_mixed_type