Fix more name_like_string. (#950)

databricks/koalas/frame.py

@@ -2358,8 +2358,8 @@ def rename(index):
                      index_name if index_name is not None else rename(i)))
                 index_map.remove(info)
 
-        new_data_scols = [
-            self._internal.scol_for(column).alias(str(name)) for column, name in new_index_map]
+        new_data_scols = [self._internal.scol_for(column).alias(name_like_string(name))
+                          for column, name in new_index_map]
 
         if len(index_map) > 0:
             index_scols = [scol_for(self._sdf, column) for column, _ in index_map]
@@ -2379,7 +2379,8 @@ def rename(index):
 
         internal = self._internal.copy(
             sdf=sdf,
-            data_columns=[str(name) for _, name in new_index_map] + self._internal.data_columns,
+            data_columns=([name_like_string(name) for _, name in new_index_map]
+                          + self._internal.data_columns),
             index_map=index_map,
             column_index=None)
 
@@ -2820,7 +2821,7 @@ def duplicated(self, subset=None, keep='first'):
             name = self._internal.index_names[0]
         else:
             name = ('0',)
-        column = str(name) if len(name) > 1 else name[0]
+        column = name_like_string(name)
 
         sdf = self._sdf
         if column == index_column:
@@ -3393,7 +3394,7 @@ def _assign(self, kwargs):
         adding_column_index = []
         for idx, scol in pairs.items():
             if idx not in set(i[:len(idx)] for i in self._internal.column_index):
-                name = str(idx) if len(idx) > 1 else idx[0]
+                name = name_like_string(idx)
                 scols.append(scol.alias(name))
                 adding_data_columns.append(name)
                 adding_column_index.append(idx)

databricks/koalas/indexes.py

@@ -35,6 +35,7 @@
 from databricks.koalas.frame import DataFrame
 from databricks.koalas.missing.indexes import _MissingPandasLikeIndex, _MissingPandasLikeMultiIndex
 from databricks.koalas.series import Series
+from databricks.koalas.utils import name_like_string
 
 
 class Index(IndexOpsMixin):
@@ -232,7 +233,7 @@ def to_series(self, name: Union[str, Tuple[str, ...]] = None) -> Series:
         kdf = self._kdf
         scol = self._scol
         if name is not None:
-            scol = scol.alias(str(name))
+            scol = scol.alias(name_like_string(name))
         column_index = [None] if len(kdf._internal.index_map) > 1 else kdf._internal.index_names
         return Series(kdf._internal.copy(scol=scol,
                                          column_index=column_index,

databricks/koalas/internal.py

@@ -727,14 +727,15 @@ def from_pandas(pdf: pd.DataFrame) -> '_InternalFrame':
                              for i, name in enumerate(index.names)]
         else:
             name = index.name
-            index_map = [(str(name) if name is not None else SPARK_INDEX_NAME_FORMAT(0),
+            index_map = [(name_like_string(name)
+                          if name is not None else SPARK_INDEX_NAME_FORMAT(0),
                           name if name is None or isinstance(name, tuple) else (name,))]
 
         index_columns = [index_column for index_column, _ in index_map]
 
         reset_index = pdf.reset_index()
         reset_index.columns = index_columns + data_columns
-        schema = StructType([StructField(str(name), infer_pd_series_spark_type(col),
+        schema = StructType([StructField(name_like_string(name), infer_pd_series_spark_type(col),
                                          nullable=bool(col.isnull().any()))
                              for name, col in reset_index.iteritems()])
         for name, col in reset_index.iteritems():

databricks/koalas/namespace.py

@@ -1515,11 +1515,12 @@ def concat(objs, axis=0, join='outer', ignore_index=False):
                 # TODO: NaN and None difference for missing values. pandas seems filling NaN.
                 sdf = kdf._sdf
                 for idx in columns_to_add:
-                    sdf = sdf.withColumn(str(idx), F.lit(None))
+                    sdf = sdf.withColumn(name_like_string(idx), F.lit(None))
 
                 kdf = DataFrame(kdf._internal.copy(
                     sdf=sdf,
-                    data_columns=kdf._internal.data_columns + [str(idx) for idx in columns_to_add],
+                    data_columns=(kdf._internal.data_columns
+                                  + [name_like_string(idx) for idx in columns_to_add]),
                     column_index=kdf._internal.column_index + columns_to_add))
 
                 kdfs.append(kdf[merged_columns])