address reviews

Author: galipremsagar

python/cudf/cudf/core/column/column.py

@@ -1012,8 +1012,6 @@ def _dispatch_subclass_from_dtype(dtype: DtypeObj) -> type[ColumnBase]:
         if is_dtype_obj_numeric(dtype, include_decimal=False):
             return cudf.core.column.NumericalColumn
 
-        if dtype_kind == "U":
-            return cudf.core.column.StringColumn
         raise TypeError(f"Unrecognized dtype: {dtype}")
 
     @staticmethod

python/cudf/cudf/core/column/numerical.py

@@ -646,13 +646,7 @@ def as_string_column(self, dtype: DtypeObj) -> StringColumn:
                 cudf.core.column.string.StringColumn,
                 ColumnBase.create(conv_func(col.plc_column), dtype),
             )
-        if self.dtype == np.dtype(np.float32):
-            # Collapse float32 artifacts like 0.100000001 -> 0.1.
-            # https://github.com/pandas-dev/pandas/pull/36464
-            result = result.replace_with_backrefs(
-                r"^([+-]?[0-9]+(?:\.[0-9]*?[1-9])?)0{6,}[0-9]+$",
-                r"\1",
-            )
+
         return result
 
     def _as_temporal_column(self, dtype: np.dtype) -> plc.Column:

python/cudf/cudf/core/series.py

@@ -90,18 +90,6 @@ def _format_percentile_names(percentiles: np.ndarray) -> list[str]:
     return [f"{int(x * 100)}%" for x in percentiles]
 
 
-def _is_simple_str_lambda(func: Any) -> bool:
-    code = getattr(func, "__code__", None)
-    return (
-        callable(func)
-        and getattr(func, "__name__", None) == "<lambda>"
-        and code is not None
-        and code.co_argcount == 1
-        and code.co_names == ("str",)
-        and code.co_consts == (None,)
-    )
-
-
 def _describe_numeric(obj: Series, percentiles: np.ndarray) -> dict[str, Any]:
     # Helper for Series.describe with numerical data.
     return {
@@ -1273,7 +1261,7 @@ def map(self, arg, na_action: None | Literal["ignore"] = None) -> Self:
             result = res["s"]
             result.name = self.name
             result.index = self.index
-        elif arg is str or _is_simple_str_lambda(arg):
+        elif arg is str:
             if self.dtype.kind == "M":
                 from cudf.core.column.datetime import (
                     _dtype_to_format_conversion,
@@ -2650,7 +2638,7 @@ def apply(
             raise ValueError("Series.apply only supports convert_dtype=True")
         elif by_row != "compat":
             raise NotImplementedError("by_row is currently not supported.")
-        elif func is str or _is_simple_str_lambda(func):
+        elif func is str:
             result = self.map(func)
             result.name = self.name
             return result