code: def drop(self, index=None, columns=None):
          
          if self._is_transposed:
              return self.transpose().drop(index=columns, columns=index).transpose()
          if index is None:
              new_data = self.data
              new_index = self.index
          else:
  
              def delitem(df, internal_indices=[]):
                  return df.drop(index=df.index[internal_indices])
  
              numeric_indices = list(self.index.get_indexer_for(index))
              new_data = self.data.apply_func_to_select_indices(
                  1, delitem, numeric_indices, keep_remaining=True
              )
              # We can't use self.index.drop with duplicate keys because in Pandas
              # it throws an error.
              new_index = self.index[~self.index.isin(index)]
          if columns is None:
              new_columns = self.columns
              new_dtypes = self.dtypes
          else:
  
              def delitem(df, internal_indices=[]):
                  return df.drop(columns=df.columns[internal_indices])
  
              numeric_indices = list(self.columns.get_indexer_for(columns))
              new_data = new_data.apply_func_to_select_indices(
                  0, delitem, numeric_indices, keep_remaining=True
              )
  
              new_columns = self.columns[~self.columns.isin(columns)]
              new_dtypes = self.dtypes.drop(columns)
          return self.__constructor__(new_data, new_index, new_columns, new_dtypes)
docs: Remove row data for target index and columns.
  
          Args:
              index: Target index to drop.
              columns: Target columns to drop.
  
          Returns:
              A new QueryCompiler.