Add test

Author: phofl

pandas/_libs/groupby.pyx

@@ -985,7 +985,7 @@ def group_nth(rank_t[:, :] out,
               int64_t[:] counts,
               ndarray[rank_t, ndim=2] values,
               const int64_t[:] labels,
-              int64_t min_count=0, int64_t rank=1
+              int64_t min_count=1, int64_t rank=1
               ):
     """
     Only aggregates on axis=0

pandas/core/groupby/groupby.py

@@ -1654,19 +1654,19 @@ def prod(self, numeric_only: bool = True, min_count: int = 0):
             numeric_only=numeric_only, min_count=min_count, alias="prod", npfunc=np.prod
         )
 
-    @doc(_groupby_agg_method_template, fname="min", no=False, mc=-1)
+    @doc(_groupby_agg_method_template, fname="min", no=False, mc=1)
     def min(self, numeric_only: bool = False, min_count: int = 1):
         return self._agg_general(
             numeric_only=numeric_only, min_count=min_count, alias="min", npfunc=np.min
         )
 
-    @doc(_groupby_agg_method_template, fname="max", no=False, mc=-1)
+    @doc(_groupby_agg_method_template, fname="max", no=False, mc=1)
     def max(self, numeric_only: bool = False, min_count: int = 1):
         return self._agg_general(
             numeric_only=numeric_only, min_count=min_count, alias="max", npfunc=np.max
         )
 
-    @doc(_groupby_agg_method_template, fname="first", no=False, mc=-1)
+    @doc(_groupby_agg_method_template, fname="first", no=False, mc=1)
     def first(self, numeric_only: bool = False, min_count: int = 1):
         def first_compat(obj: FrameOrSeries, axis: int = 0):
             def first(x: Series):
@@ -1690,7 +1690,7 @@ def first(x: Series):
             npfunc=first_compat,
         )
 
-    @doc(_groupby_agg_method_template, fname="last", no=False, mc=-1)
+    @doc(_groupby_agg_method_template, fname="last", no=False, mc=1)
     def last(self, numeric_only: bool = False, min_count: int = 1):
         def last_compat(obj: FrameOrSeries, axis: int = 0):
             def last(x: Series):

pandas/tests/groupby/aggregate/test_cython.py

@@ -166,23 +166,23 @@ def test__cython_agg_general(op, targop):
 
 
 @pytest.mark.parametrize(
-    "op, targop",
+    "op, targop, kwargs",
     [
-        ("mean", np.mean),
-        ("median", lambda x: np.median(x) if len(x) > 0 else np.nan),
-        ("var", lambda x: np.var(x, ddof=1)),
-        ("min", np.min),
-        ("max", np.max),
+        ("mean", np.mean, {}),
+        ("median", lambda x: np.median(x) if len(x) > 0 else np.nan, {}),
+        ("var", lambda x: np.var(x, ddof=1), {}),
+        ("min", np.min, {"min_count": 1}),
+        ("max", np.max, {"min_count": 1}),
     ],
 )
-def test_cython_agg_empty_buckets(op, targop, observed):
+def test_cython_agg_empty_buckets(op, targop, kwargs, observed):
     df = DataFrame([11, 12, 13])
     grps = range(0, 55, 5)
 
     # calling _cython_agg_general directly, instead of via the user API
     # which sets different values for min_count, so do that here.
     g = df.groupby(pd.cut(df[0], grps), observed=observed)
-    result = g._cython_agg_general(op)
+    result = g._cython_agg_general(op, **kwargs)
 
     g = df.groupby(pd.cut(df[0], grps), observed=observed)
     expected = g.agg(lambda x: targop(x))

pandas/tests/groupby/aggregate/test_other.py

@@ -638,3 +638,12 @@ def weird_func(x):
 
     result = df["decimals"].groupby(df["id1"]).agg(weird_func)
     tm.assert_series_equal(result, expected, check_names=False)
+
+
+@pytest.mark.parametrize("func", ["first", "last", "max", "min"])
+def test_min_count_implementation_min_max_first_last(func):
+    # GH#37821
+    df = DataFrame({"a": [1] * 3, "b": [np.nan] * 3})
+    result = getattr(df.groupby("a"), func)(min_count=2)
+    expected = DataFrame({"b": [np.nan]}, index=Index([1], name="a"))
+    tm.assert_frame_equal(result, expected)