diff --git a/stats.py b/stats.py
index 2d7f191..5be4c35 100644
--- a/stats.py
+++ b/stats.py
@@ -25,6 +25,8 @@
     - CRNs to exclude, for example SP20, because of covid. Possibly SU20 and FA20
     - CRNs in which teacher has done more than the minimum training in online teaching
 
+- Next steps: generate the x-reference for what categories teachers are in, and
+  integrate into the main data file.
 
 ## Hypothesis Testing
 
@@ -144,7 +146,12 @@ def short_name_to_crn(name):
         #print("Exception: ", e, name)
         return to_crn_fallback(name)
 
-def short_name_to_teacher(name):
+
+def fixname(n):
+    return re.sub(r'\s+',' ', n).strip()
+
+
+def short_name_to_teacher_type_crn_sem(name):
     load_schedules()
     crn, sem = short_name_to_crn(name)
 
@@ -155,11 +162,11 @@ def short_name_to_teacher(name):
                 sem = 'sp' + sem[2:]
             for course in schedules[sem]:
                 if course['crn'] == crn:
-                    return course['teacher'], course['type']
+                    return fixname(course['teacher']), course['type'], crn, sem
     except Exception as e:
-        return None
+        return None, None, None, None
 
-    return None
+    return None, None, None, None
 
 
 
@@ -169,13 +176,13 @@ def nametest():
         next(csvreader)
 
         for row in csvreader:
-            print(row[0], "-", short_name_to_teacher(row[0]))
+            print(row[0], "-", short_name_to_teacher_type_crn_sem(row[0]))
             next(csvreader)
 
-
-
-def count_above_70(li):
-    pass
+def above_70(li,maximum):
+    cutoff = 0.7 * maximum
+    above = list(filter(lambda x: x >= cutoff, li))
+    return (len(above)/len(li)) 
 
 def process_one_course_grades(block, output):
     fxns = [mean, median, stdev, min, max, len]
@@ -184,25 +191,32 @@ def process_one_course_grades(block, output):
     course_code = block[0][2]
     cur_scores = [num(x[6]) for x in block]
     final_scores = [num(x[7]) for x in block]
+    print(course_code)
+    teacher, mode, crn, sem2 = short_name_to_teacher_type_crn_sem(course_code)
+    if not teacher:
+        return
     #print(cur_scores)
     #print(final_scores)
     try:
         (cur_mean, cur_median, cur_stdev, cur_min, cur_max, cur_count) = [round(f(cur_scores)) for f in fxns]
         (final_mean, final_median, final_stdev, final_min, final_max, final_count) = [round(f(final_scores)) for f in fxns]
 
-        print("Course            mean  median  stdev   min    max     count")
-        print("{:>12}   {: 6.0f}   {: 6.0f}   {: 6.0f}   {: 6.0f}   {: 6.0f}   {:6d}   ".format(course_code, cur_mean, cur_median, cur_stdev, cur_min, cur_max, cur_count))
-        print("{:>12}   {: 6.0f}   {: 6.0f}   {: 6.0f}   {: 6.0f}   {: 6.0f}   {:6d}   ".format(course_code, final_mean, final_median, final_stdev, final_min, final_max, final_count))
+        cur_pct_passed = above_70(cur_scores, cur_max)
+        final_pct_passed = above_70(final_scores, final_max)
+
+        print("Course            % > 70  mean  median  stdev   min    max     count")
+        print("{:>12}   {: 6.0f}   {: 6.0f}   {: 6.0f}   {: 6.0f}   {: 6.0f}   {: 6.0f}   {:6d}   ".format(course_code, cur_pct_passed, cur_mean, cur_median, cur_stdev, cur_min, cur_max, cur_count))
+        print("{:>12}   {: 6.0f}   {: 6.0f}   {: 6.0f}   {: 6.0f}   {: 6.0f}   {: 6.0f}   {:6d}   ".format(course_code, final_pct_passed, final_mean, final_median, final_stdev, final_min, final_max, final_count))
         print()
-        output.writerow( [course_code, "current score", cur_mean, cur_median, cur_stdev, cur_min, cur_max, cur_count] )
-        output.writerow( [course_code, "final score", final_mean, final_median, final_stdev, final_min, final_max, final_count] )
+        #output.writerow( [sem2, crn, course_code, "current score", teacher, mode, cur_pct_passed, cur_mean, cur_median, cur_stdev, cur_min, cur_max, cur_count] )
+        output.writerow( [sem2, crn, course_code, "final score", teacher, mode, final_pct_passed, final_mean, final_median, final_stdev, final_min, final_max, final_count] )
     except Exception as e:
         print("Exception:", e)
 
 def process_grades():
     with open(all_courses_file, "w", newline="") as output_f:
         output = csv.writer(output_f)
-        output.writerow("Course mean median stdev min max count".split(" "))
+        output.writerow("sem crn shortname score_type teacher mode percent_passed mean median stdev min max count".split(" "))
 
         with open(all_grades_file, newline="") as csvfile:
             csvreader = csv.reader(csvfile)