diff --git a/Orange/widgets/unsupervised/owhierarchicalclustering.py b/Orange/widgets/unsupervised/owhierarchicalclustering.py
index a831d6eb411..cbf95a97670 100644
--- a/Orange/widgets/unsupervised/owhierarchicalclustering.py
+++ b/Orange/widgets/unsupervised/owhierarchicalclustering.py
@@ -5,7 +5,7 @@
 from itertools import chain
 from contextlib import contextmanager
 
-import numpy
+import numpy as np
 
 from AnyQt.QtWidgets import (
     QGraphicsWidget, QGraphicsObject, QGraphicsLinearLayout, QGraphicsPathItem,
@@ -34,7 +34,7 @@
 from Orange.widgets.utils import colorpalette, itemmodels
 from Orange.widgets.utils.annotated_data import (create_annotated_table,
                                                  ANNOTATED_DATA_SIGNAL_NAME)
-from Orange.widgets.widget import Input, Output
+from Orange.widgets.widget import Input, Output, Msg
 
 __all__ = ["OWHierarchicalClustering"]
 
@@ -605,7 +605,7 @@ def _rescale(self):
         else:
             drect = QSizeF(leaf_count, self._root.value.height)
 
-        eps = numpy.finfo(numpy.float64).eps
+        eps = np.finfo(np.float64).eps
 
         if abs(drect.width()) < eps:
             sx = 1.0
@@ -763,6 +763,9 @@ class Outputs:
     cluster_roles = ["Attribute", "Class variable", "Meta variable"]
     basic_annotations = ["None", "Enumeration"]
 
+    class Error(widget.OWWidget.Error):
+        not_finite_distances = Msg("Some distances are infinite")
+
     def __init__(self):
         super().__init__()
 
@@ -962,11 +965,16 @@ def axis_view(orientation):
     @Inputs.distances
     def set_distances(self, matrix):
         self.error()
+        self.Error.clear()
         if matrix is not None:
             N, _ = matrix.shape
             if N < 2:
                 self.error("Empty distance matrix")
                 matrix = None
+        if matrix is not None:
+            if not np.all(np.isfinite(matrix)):
+                self.Error.not_finite_distances()
+                matrix = None
 
         self.matrix = matrix
         if matrix is not None:
@@ -1135,7 +1143,7 @@ def commit(self):
 
         if isinstance(items, Orange.data.Table) and self.matrix.axis == 1:
             # Select rows
-            c = numpy.zeros(self.matrix.shape[0])
+            c = np.zeros(self.matrix.shape[0])
 
             for i, indices in enumerate(maps):
                 c[indices] = i
diff --git a/Orange/widgets/unsupervised/tests/test_owhierarchicalclustering.py b/Orange/widgets/unsupervised/tests/test_owhierarchicalclustering.py
index 588ac41734a..99699fa2f55 100644
--- a/Orange/widgets/unsupervised/tests/test_owhierarchicalclustering.py
+++ b/Orange/widgets/unsupervised/tests/test_owhierarchicalclustering.py
@@ -1,7 +1,8 @@
 # Test methods with long descriptive names can omit docstrings
 # pylint: disable=missing-docstring
-import numpy
+import numpy as np
 import Orange.misc
+from Orange.data import Table, Domain, ContinuousVariable, DiscreteVariable
 from Orange.distance import Euclidean
 from Orange.widgets.tests.base import WidgetTest, WidgetOutputsTestMixin
 from Orange.widgets.unsupervised.owhierarchicalclustering import \
@@ -53,7 +54,7 @@ def test_selection_box_output(self):
         self.assertIsNone(self.get_output(self.widget.Outputs.annotated_data))
 
     def test_all_zero_inputs(self):
-        d = Orange.misc.DistMatrix(numpy.zeros((10, 10)))
+        d = Orange.misc.DistMatrix(np.zeros((10, 10)))
         self.widget.set_distances(d)
 
     def test_annotation_settings_retrieval(self):
@@ -61,8 +62,8 @@ def test_annotation_settings_retrieval(self):
         widget = self.widget
 
         dist_names = Orange.misc.DistMatrix(
-            numpy.zeros((4, 4)), self.data, axis=0)
-        dist_no_names = Orange.misc.DistMatrix(numpy.zeros((10, 10)), axis=1)
+            np.zeros((4, 4)), self.data, axis=0)
+        dist_no_names = Orange.misc.DistMatrix(np.zeros((10, 10)), axis=1)
 
         self.send_signal(self.widget.Inputs.distances, self.distances)
         # Check that default is set (class variable)
@@ -102,3 +103,23 @@ def test_domain_loses_class(self):
         data = self.data[:, :4]
         distances = Euclidean(data)
         self.send_signal(self.widget.Inputs.distances, distances)
+
+    def test_infinite_distances(self):
+        """
+        Scipy does not accept infinite distances and neither does this widget.
+        Error is shown.
+        GH-2380
+        """
+        table = Table(
+            Domain(
+                [ContinuousVariable("a")],
+                [DiscreteVariable("b", values=["y"])]),
+            list(zip([1.79e308, -1e120],
+                     "yy"))
+        )
+        distances = Euclidean(table)
+        self.assertFalse(self.widget.Error.not_finite_distances.is_shown())
+        self.send_signal(self.widget.Inputs.distances, distances)
+        self.assertTrue(self.widget.Error.not_finite_distances.is_shown())
+        self.send_signal(self.widget.Inputs.distances, self.distances)
+        self.assertFalse(self.widget.Error.not_finite_distances.is_shown())