diff --git a/python/cudf_polars/cudf_polars/dsl/ir.py b/python/cudf_polars/cudf_polars/dsl/ir.py
index cce0c4a3d94..488de7aaa02 100644
--- a/python/cudf_polars/cudf_polars/dsl/ir.py
+++ b/python/cudf_polars/cudf_polars/dsl/ir.py
@@ -30,7 +30,7 @@
 
 import cudf_polars.dsl.expr as expr
 from cudf_polars.containers import DataFrame, NamedColumn
-from cudf_polars.utils import sorting
+from cudf_polars.utils import dtypes, sorting
 
 if TYPE_CHECKING:
     from collections.abc import MutableMapping
@@ -1044,6 +1044,32 @@ class HConcat(IR):
     def evaluate(self, *, cache: MutableMapping[int, DataFrame]) -> DataFrame:
         """Evaluate and return a dataframe."""
         dfs = [df.evaluate(cache=cache) for df in self.dfs]
+        max_rows = max(df.num_rows for df in dfs)
+        # Horizontal concatenation extends shorter tables with nulls
+        dfs = [
+            df
+            if df.num_rows == max_rows
+            else DataFrame.from_table(
+                plc.concatenate.concatenate(
+                    [
+                        df.table,
+                        plc.Table(
+                            [
+                                plc.Column.from_scalar(
+                                    plc.interop.from_arrow(
+                                        pa.scalar(None, type=dtypes.arrow_type(c.obj))
+                                    ),
+                                    max_rows - df.num_rows,
+                                )
+                                for c in df.columns
+                            ]
+                        ),
+                    ]
+                ),
+                df.column_names,
+            )
+            for df in dfs
+        ]
         return DataFrame(
             list(itertools.chain.from_iterable(df.columns for df in dfs)),
         )
diff --git a/python/cudf_polars/cudf_polars/utils/dtypes.py b/python/cudf_polars/cudf_polars/utils/dtypes.py
index 9db41d641bf..81a98508d6e 100644
--- a/python/cudf_polars/cudf_polars/utils/dtypes.py
+++ b/python/cudf_polars/cudf_polars/utils/dtypes.py
@@ -106,14 +106,19 @@ def arrow_type(column: plc.Column) -> pa.DataType:
         For unsupported conversions.
     """
     dtype = column.type()
-    if dtype.id() == plc.TypeId.LIST:
+    tid = dtype.id()
+    if tid == plc.TypeId.LIST:
         _, inner = column.children()
         return plc.interop.to_arrow(dtype, value_type=arrow_type(inner))
-    elif plc.traits.is_fixed_width(dtype) and not plc.traits.is_fixed_point(dtype):
+    elif (
+        (plc.traits.is_fixed_width(dtype) and not plc.traits.is_fixed_point(dtype))
+        or tid == plc.TypeId.STRING
+        or tid == plc.TypeId.EMPTY
+    ):
         return plc.interop.to_arrow(dtype)
     else:
         raise NotImplementedError(
-            "No conversion for struct columns"
+            f"No conversion for columns with type {tid}"
         )  # pragma: no cover; unreachable since we raise earlier