diff --git a/data/validation+testing/number_check.py b/data/validation+testing/number_check.py
index 5016cfe..b50f7dd 100644
--- a/data/validation+testing/number_check.py
+++ b/data/validation+testing/number_check.py
@@ -12,20 +12,20 @@ def main():
     enriched_rui_locations = load_json("../enriched_rui_locations.jsonld")
     corridors = load_json("../corridors.jsonld")
 
-
-
     # unqiue rui locations, datasets, and cell types
+    # dict for corridors and associated AS
     unique_rui_locations = set()
     unique_datasets = set()
     unique_cell_types = set()
     unique_as_in_corridors = set()
-    
+    as_counts_in_corridor = {}
+
     # get unique datasets and cell types
     for cell_summary in dataset_cell_summaries['@graph']:
         unique_datasets.add(cell_summary['cell_source'])
         for row in cell_summary['summary']:
             unique_cell_types.add(row['cell_id'])
-    
+
     # get AS that collide with tissue blocks that form corridors
     for donor in enriched_rui_locations['@graph']:
         for sample in donor['samples']:
@@ -33,8 +33,18 @@ def main():
                 for collision_item in sample['rui_location']['all_collisions']:
                     for collision in collision_item['collisions']:
                         unique_as_in_corridors.add(collision['as_3d_id'])
-    
-    
+
+    # get numbers of AS per corridor
+    for donor in enriched_rui_locations['@graph']:
+        for sample in donor['samples']:
+            if "corridor" in sample['rui_location']:
+                as_counts_in_corridor[sample['rui_location']
+                                      ['corridor']['file']] = []
+                for collision_item in sample['rui_location']['all_collisions']:
+                    for collision in collision_item['collisions']:
+                        as_counts_in_corridor[sample['rui_location']['corridor']['file']].append(collision['as_3d_id'])
+
+    # print results for unique counts
     print(f'''
           Unique datasets: {len(unique_datasets)}
           Unique cell types: {len(unique_cell_types)}
@@ -42,8 +52,13 @@ def main():
           Unique tissue blocks: {len(count_tissue_blocks(enriched_rui_locations))}
           Unique AS in corridors: {len(unique_as_in_corridors)}
           ''')
-        
-    # covering which unique eorgans
+
+    # print result for AS per corridor
+    for key in as_counts_in_corridor:
+        print(f'''Corridor {key} has {len(as_counts_in_corridor[key])} AS: ''')
+        for anatomical_structure in as_counts_in_corridor[key]:
+            print(f'''\tThose AS are: {anatomical_structure} AS: ''')
+
 
 def count_tissue_blocks(response):
     """A function to count unique tissue blocks
@@ -61,9 +76,10 @@ def count_tissue_blocks(response):
                 result.add(sample['@id'])
             except:
                 continue
-    
+
     return result
-    
+
+
 def count_rui_locations(response):
     """A function to count unique rui locations
 
@@ -73,7 +89,7 @@ def count_rui_locations(response):
     Returns:
         set: A set of unique RUI location IDs
     """
-    
+
     result = set()
     for donor in response['@graph']:
         for sample in donor['samples']:
@@ -81,9 +97,10 @@ def count_rui_locations(response):
                 result.add(sample['rui_location']['@id'])
             except:
                 continue
-    
+
     return result
 
+
 def load_json(file_path):
     """A function to load a json file and return the data as a dict