BUG: Min/max does not work for dates with timezones if there are missing values in the data frame

doc/source/whatsnew/v1.4.0.rst

@@ -538,7 +538,7 @@ Missing
 ^^^^^^^
 - Bug in :meth:`DataFrame.fillna` with limit and no method ignores axis='columns' or ``axis = 1`` (:issue:`40989`)
 - Bug in :meth:`DataFrame.fillna` not replacing missing values when using a dict-like ``value`` and duplicate column names (:issue:`43476`)
--
+- Bug in :meth:`DataFrame.max`, :meth:`DataFrame.min`, :meth:`Series.max` and :meth:`Series.min` when called on datetime columns with timezone aware data and missing elements (:issue:`27794` and :issue:`44196`)
 
 MultiIndex
 ^^^^^^^^^^

pandas/core/frame.py

@@ -10033,6 +10033,7 @@ def _get_data() -> DataFrame:
             data = _get_data()
             labels = data._get_agg_axis(axis)
 
+            # do we need this line?
             values = data.values
             with np.errstate(all="ignore"):
                 result = func(values)

pandas/core/nanops.py

@@ -1039,7 +1039,20 @@ def reduction(
             except (AttributeError, TypeError, ValueError):
                 result = np.nan
         else:
-            result = getattr(values, meth)(axis)
+            try:
+                result = getattr(values, meth)(axis)
+            except TypeError as e:
+                # the only case when this can happein is for timezone aware
+                # Timestamps  where a NaT value is casted to # np.inf
+                from pandas.core.dtypes.common import is_float
+
+                vfunc = np.vectorize(lambda x: is_float(x))
+                mask = vfunc(values)
+                if mask.any():
+                    values = np.where(mask, NaT, values)
+                    result = getattr(values, meth)(axis)
+                else:
+                    raise e
 
         result = _maybe_null_out(result, axis, mask, values.shape)
         return result

pandas/tests/groupby/aggregate/test_other.py

@@ -674,3 +674,63 @@ def weird_func(x):
 
     result = df["decimals"].groupby(df["id1"]).agg(weird_func)
     tm.assert_series_equal(result, expected, check_names=False)
+
+
+def test_timezone_min_max_with_nat():
+    # GH#27794
+    df = pd.concat(
+        [
+            pd.date_range(start="2018-01-01", end="2018-01-03")
+            .to_series()
+            .dt.tz_localize("UTC"),
+            pd.date_range(start="2018-01-01", end="2018-01-02")
+            .to_series()
+            .dt.tz_localize("UTC"),
+        ],
+        axis=1,
+    )
+
+    expected = pd.Series(
+        [
+            pd.Timestamp("2018-01-01", tz="UTC"),
+            pd.Timestamp("2018-01-02", tz="UTC"),
+            pd.NaT,
+        ],
+        index=pd.date_range(start="2018-01-01", end="2018-01-03"),
+    )
+    result = df.min(axis=1)
+    tm.assert_series_equal(result, expected)
+
+    expected = pd.Series(
+        [
+            pd.Timestamp("2018-01-01", tz="UTC"),
+            pd.Timestamp("2018-01-02", tz="UTC"),
+            pd.NaT,
+        ],
+        index=pd.date_range(start="2018-01-01", end="2018-01-03"),
+    )
+    result = df.max(axis=1)
+    tm.assert_series_equal(result, expected)
+
+
+def test_min_max_timezone_nat2():
+    # GH#44196
+    rng_with_tz = pd.date_range(
+        start="2021-10-01T12:00:00+02:00", end="2021-10-02T12:00:00+02:00", freq="4H"
+    )
+    df_with_tz = pd.DataFrame(
+        data={"A": rng_with_tz, "B": rng_with_tz + pd.Timedelta(minutes=20)}
+    )
+    df_with_tz.iloc[2, 1] = pd.NaT
+
+    result = df_with_tz.max(axis=1)
+    expected = pd.Series([
+        pd.Timestamp('2021-10-01T12:20:00+02:00'),
+        pd.Timestamp('2021-10-01T16:20:00+02:00'),
+        pd.NaT,
+        pd.Timestamp('2021-10-02T00:20:00+02:00'),
+        pd.Timestamp('2021-10-02T04:20:00+02:00'),
+        pd.Timestamp('2021-10-02T08:20:00+02:00'),
+        pd.Timestamp('2021-10-02T12:20:00+02:00'),
+    ])
+    tm.assert_series_equal(result, expected)

pandas/tests/indexes/datetimes/test_date_range.py

@@ -746,7 +746,7 @@ def test_cached_range_bug(self):
         assert len(rng) == 50
         assert rng[0] == datetime(2010, 9, 1, 5)
 
-    def test_timezone_comparaison_bug(self):
+    def test_timezone_comparison_bug(self):
         # smoke test
         start = Timestamp("20130220 10:00", tz="US/Eastern")
         result = date_range(start, periods=2, tz="US/Eastern")