diff --git a/awswrangler/pandas.py b/awswrangler/pandas.py
index ac4c7c8ac..d0f6dd0b0 100644
--- a/awswrangler/pandas.py
+++ b/awswrangler/pandas.py
@@ -1004,7 +1004,7 @@ def _data_to_s3_dataset_writer(dataframe: pd.DataFrame,
             objects_paths.append(object_path)
         else:
             dataframe = Pandas._cast_pandas(dataframe=dataframe, cast_columns=cast_columns)
-            for keys, subgroup in dataframe.groupby(partition_cols):
+            for keys, subgroup in dataframe.groupby(by=partition_cols, observed=True):
                 subgroup = subgroup.drop(partition_cols, axis="columns")
                 if not isinstance(keys, tuple):
                     keys = (keys, )
@@ -1407,7 +1407,7 @@ def read_parquet(self,
         if len(dfs) == 1:
             df: pd.DataFrame = dfs[0]
         else:
-            df = pd.concat(objs=dfs, ignore_index=True)
+            df = pd.concat(objs=dfs, ignore_index=True, sort=False)
         return df
 
     @staticmethod
@@ -1870,7 +1870,7 @@ def read_csv_list(
                     logger.debug(f"Closing proc number: {i}")
                     receive_pipes[i].close()
                 logger.debug(f"Concatenating all {len(paths)} DataFrames...")
-                df = pd.concat(objs=dfs, ignore_index=True)
+                df = pd.concat(objs=dfs, ignore_index=True, sort=False)
             return df
 
     def _read_csv_list_iterator(
diff --git a/testing/test_awswrangler/test_pandas.py b/testing/test_awswrangler/test_pandas.py
index beb51d0b7..f0d3a3819 100644
--- a/testing/test_awswrangler/test_pandas.py
+++ b/testing/test_awswrangler/test_pandas.py
@@ -2173,3 +2173,16 @@ def test_aurora_mysql_load_special2(bucket, mysql_parameters):
         assert rows[0][2] is None
         assert rows[1][3] is None
     conn.close()
+
+
+def test_to_parquet_categorical_partitions(bucket):
+    path = f"s3://{bucket}/test_to_parquet_categorical_partitions"
+    wr.s3.delete_objects(path=path)
+    d = pd.date_range("1990-01-01", freq="D", periods=10000)
+    vals = pd.np.random.randn(len(d), 4)
+    x = pd.DataFrame(vals, index=d, columns=["A", "B", "C", "D"])
+    x['Year'] = x.index.year
+    x['Year'] = x['Year'].astype('category')
+    wr.pandas.to_parquet(x[x.Year == 1990], path=path, partition_cols=["Year"])
+    y = wr.pandas.read_parquet(path=path)
+    assert len(x[x.Year == 1990].index) == len(y.index)