add whatsnew + test + changed logic

Author: mroeschke

doc/source/whatsnew/v0.20.0.txt

@@ -279,7 +279,7 @@ Performance Improvements
 
 - Improved performance of ``pd.wide_to_long()`` (:issue:`14779`)
 - Increased performance of ``pd.factorize()`` by releasing the GIL with ``object`` dtype when inferred as strings (:issue:`14859`)
-
+- Increased performance of ``groupby().cummin()`` and ``groupby().cummax()`` (:issue:`15048`)
 
 
 .. _whatsnew_0200.bug_fixes:

pandas/src/algos_groupby_helper.pxi.in

@@ -695,10 +695,10 @@ def group_cummin(numeric[:, :] out,
                 if val == val:
                     if j == 0:
                         min_val = val
-                    elif val < min_val:
+                    elif val < accum[lab, j]:
                         min_val = val
                     accum[lab, j] = min_val
-                    out[i, j] = accum[lab, j]
+                    out[i, j] = min_val
 
 
 @cython.boundscheck(False)
@@ -729,7 +729,7 @@ def group_cummax(numeric[:, :] out,
                 if val == val:
                     if j == 0:
                         max_val = val
-                    elif val > max_val:
+                    elif val > accum[lab, j]:
                         max_val = val
                     accum[lab, j] = max_val
                     out[i, j] = accum[lab, j]

pandas/tests/groupby/test_groupby.py

@@ -4977,8 +4977,6 @@ def test_groupby_whitelist(self):
             'max',
             'head',
             'tail',
-            'cumsum',
-            'cumprod',
             'cumcount',
             'resample',
             'describe',
@@ -5016,8 +5014,6 @@ def test_groupby_whitelist(self):
             'max',
             'head',
             'tail',
-            'cumsum',
-            'cumprod',
             'cumcount',
             'resample',
             'describe',
@@ -5773,6 +5769,17 @@ def test_agg_over_numpy_arrays(self):
 
         assert_frame_equal(result, expected)
 
+    def test_cummin_cummax(self):
+        df = pd.DataFrame({'A': np.random.randint(0, 5, size=100),
+                           'B': np.random.randn(100)})
+        result = df.groupby('A').cummin()
+        expected = df.groupby('A').apply(np.minimum.accumulate)['B'].to_frame()
+        tm.assert_frame_equal(result, expected)
+
+        result = df.groupby('A').cummax()
+        expected = df.groupby('A').apply(np.maximum.accumulate)['B'].to_frame()
+        tm.assert_frame_equal(result, expected)
+
 
 def assert_fp_equal(a, b):
     assert (np.abs(a - b) < 1e-12).all()