diff --git a/rapids/views.py b/rapids/views.py
index 1a192291..6df84da2 100755
--- a/rapids/views.py
+++ b/rapids/views.py
@@ -580,6 +580,119 @@ def mark_all(request, exam_pk, sk):
 def mark_review(request, exam_pk, sk):
     return mark(request, exam_pk, sk, unmarked_exam_answers_only=False, review=True)
 
+@login_required
+def exam_scores_cid2(request, pk):
+    exam = get_object_or_404(Exam, pk=pk)
+
+    if not exam.exam_mode:
+        raise Http404("Packet not in exam mode")
+
+    user_answers_and_marks = defaultdict(list)
+    user_answers_marks = defaultdict(list)
+    user_answers = defaultdict(list)
+    user_names = {}
+
+    by_question = defaultdict(list)
+    unmarked = set()
+
+    questions = exam.exam_questions.all()
+
+    cids = (
+        CidUserAnswer.objects.filter(question__in=questions, exam__id=pk)
+    )
+
+
+    # Loop through all candidates
+    for cid_user_answer in cids:
+        # Convoluted (probably...)
+        cid = cid_user_answer.cid
+        s = cid_user_answer
+        user_names[cid] = cid
+
+        q = cid_user_answer.question
+
+
+        if not s:
+            # skip if no answer
+            user_answers_marks[cid].append(0)
+            user_answers[cid].append("")
+            by_question[q].append(("", 0))
+            continue
+        elif s.normal:
+            ans = "Normal"
+        else:
+            ans = s.answer
+        answer_score = s.get_answer_score()
+        if answer_score == "unmarked":
+            index = exam.get_question_index(q)
+            unmarked.add(index)
+        user_answers[cid].append(ans)
+        user_answers_marks[cid].append(answer_score)
+        user_answers_and_marks[cid].append((ans, answer_score))
+
+        by_question[q].append((ans, answer_score))
+
+    user_scores = {}
+    user_scores_normalised = {}
+    for user in user_answers_marks:
+        user_scores[user] = sum(
+            [i for i in user_answers_marks[user] if i != "unmarked"]
+        )
+        user_scores_normalised[user] = normaliseScore(
+            sum([i for i in user_answers_marks[user] if i != "unmarked"])
+        )
+
+    user_scores_list = list(user_scores.values())
+
+    if len(user_scores_list) < 1:
+        mean = 0
+        median = 0
+        mode = 0
+        fig_html = ""
+    else:
+        mean = statistics.mean(user_scores_list)
+        median = statistics.median(user_scores_list)
+        try:
+            mode = statistics.mode(user_scores_list)
+        except statistics.StatisticsError:
+            mode = "No unique mode"
+
+        df = user_scores_list
+        fig = px.histogram(
+            df,
+            x=0,
+            title="{}: distribution of scores".format(exam),
+            labels={"0": "Score"},
+            height=400,
+            width=600,
+        )
+        fig_html = fig.to_html()
+
+    max_score = len(questions) * 2
+
+    return render(
+        request,
+        "rapids/exam_scores.html",
+        {
+            "cids": cids,
+            "exam": exam,
+            "unmarked": unmarked,
+            "questions": questions,
+            "by_question": by_question,
+            "user_answers": dict(user_answers),
+            "user_answers_marks": dict(user_answers_marks),
+            "user_scores": user_scores,
+            "user_scores_normalised": user_scores_normalised,
+            "user_scores_list": user_scores_list,
+            "user_names": user_names,
+            "user_answers_and_marks": user_answers_and_marks,
+            "max_score": max_score,
+            "mean": mean,
+            "median": median,
+            "mode": mode,
+            "plot": fig_html,
+        },
+    )
 
 # @user_passes_test(user_is_admin, login_url="/accounts/login")
 @login_required