diff --git a/hands_on/pyanno_voting/pyanno/tests/test_voting.py b/hands_on/pyanno_voting/pyanno/tests/test_voting.py
index f21a10c..a4a420f 100644
--- a/hands_on/pyanno_voting/pyanno/tests/test_voting.py
+++ b/hands_on/pyanno_voting/pyanno/tests/test_voting.py
@@ -41,3 +41,15 @@ def test_majority_vote_empty_item():
     expected = [1, MV, 2]
     result = voting.majority_vote(annotations)
     assert result == expected
+    
+from numpy.testing import assert_array_equal
+def test_frequency_vote():
+    annotations = [
+        [1, 1, 2],
+        [-1, 1, 2],
+    ]
+    classes=4
+    expected = [0, 0.6, 0.4,0]
+    result = voting.labels_frequency(annotations,classes)
+    assert_array_equal(result,expected)
+
diff --git a/hands_on/pyanno_voting/pyanno/voting.py b/hands_on/pyanno_voting/pyanno/voting.py
index d5b5747..acd072b 100644
--- a/hands_on/pyanno_voting/pyanno/voting.py
+++ b/hands_on/pyanno_voting/pyanno/voting.py
@@ -100,3 +100,12 @@ def labels_frequency(annotations, nclasses):
         freq[k] is the frequency of elements of class k in `annotations`, i.e.
         their count over the number of total of observed (non-missing) elements
     """
+    
+    votes = np.concatenate(annotations)
+    correct_votes = votes[votes >= 0]
+    freq = np.zeros(nclasses)
+    for iClass in range(nclasses):
+    	freq[iClass] = sum(correct_votes == iClass)/len(correct_votes)
+    
+    return freq
+