From e738f7df7f53247cde1208a3242d24f4db319cdf Mon Sep 17 00:00:00 2001
From: Karthik Velayutham <karthik.velayutham@gmail.com>
Date: Mon, 23 Jan 2023 11:49:32 -0600
Subject: [PATCH] Add QC method for groupby.sem (#47) (core)

---
 .../storage_formats/base/query_compiler.py    | 22 +++++++++++++++++++
 modin/pandas/groupby.py                       | 17 +++++++++-----
 2 files changed, 34 insertions(+), 5 deletions(-)

diff --git a/modin/core/storage_formats/base/query_compiler.py b/modin/core/storage_formats/base/query_compiler.py
index 9469cd2e612..47999244345 100644
--- a/modin/core/storage_formats/base/query_compiler.py
+++ b/modin/core/storage_formats/base/query_compiler.py
@@ -2975,6 +2975,28 @@ def groupby_std(
             drop=drop,
         )
 
+    @doc_utils.doc_groupby_method(
+        action="compute standard error", result="standard error", refer_to="sem"
+    )
+    def groupby_sem(
+        self,
+        by,
+        axis,
+        groupby_kwargs,
+        agg_args,
+        agg_kwargs,
+        drop=False,
+    ):
+        return self.groupby_agg(
+            by=by,
+            agg_func="sem",
+            axis=axis,
+            groupby_kwargs=groupby_kwargs,
+            agg_args=agg_args,
+            agg_kwargs=agg_kwargs,
+            drop=drop,
+        )
+
     @doc_utils.doc_groupby_method(
         action="compute numerical rank", result="numerical rank", refer_to="rank"
     )
diff --git a/modin/pandas/groupby.py b/modin/pandas/groupby.py
index 844467ef575..e605637d150 100644
--- a/modin/pandas/groupby.py
+++ b/modin/pandas/groupby.py
@@ -222,7 +222,11 @@ def ffill(self, limit=None):
         return self._default_to_pandas(lambda df: df.ffill(limit=limit))
 
     def sem(self, ddof=1):
-        return self._default_to_pandas(lambda df: df.sem(ddof=ddof))
+        return self._wrap_aggregation(
+            type(self._query_compiler).groupby_sem,
+            agg_kwargs=dict(ddof=ddof),
+            numeric_only=True,
+        )
 
     def sample(self, n=None, frac=None, replace=False, weights=None, random_state=None):
         return self._default_to_pandas(
@@ -690,10 +694,13 @@ def do_relabel(obj_to_relabel):
                 kwargs = {}
             func = func_dict
         elif is_list_like(func):
-            return self._default_to_pandas(
-                lambda df, *args, **kwargs: df.aggregate(func, *args, **kwargs),
-                *args,
-                **kwargs,
+            return self._wrap_aggregation(
+                qc_method=type(self._query_compiler).groupby_agg,
+                numeric_only=False,
+                agg_func=func,
+                agg_args=args,
+                agg_kwargs=kwargs,
+                how="axis_wise",
             )
         elif callable(func):
             return self._check_index(