Update app.py

app.py

@@ -66,14 +66,13 @@ def get_node_info(node):
     return node_info,student_narrations,student_gen, student_rank, node_name
 
 def network_visualizer(yaxis, city, fstyear,lastyr, num_nodes):
-    edges = subsetEdges(city, fstyear, lastyr)
-    
+    edges = subsetEdges(city, fstyear, lastyr).sort_values(yaxis, ascending=False).head(num_nodes)
     G = nx.from_pandas_edgelist(edges, source = 'Teacher_ID', target = 'Student_ID', create_using = nx.DiGraph())
-    nodes = list(G.nodes)
-    node_reports = [narrator_bios[narrator_bios['Rawi ID'].astype(int) == int(x)]['Number of Narrations'].to_list()[0] for x in nodes]
-    nodes_df = pd.DataFrame({'Node': nodes, 'Report': node_reports}).sort_values('Report', ascending=False).head(num_nodes)
-    nodes_remove = list(set(nodes) - set(nodes_df['Node'].to_list()))
-    [G.remove_nodes_from(nodes_remove)]
+    # nodes = list(G.nodes)
+    # node_reports = [narrator_bios[narrator_bios['Rawi ID'].astype(int) == int(x)]['Number of Narrations'].to_list()[0] for x in nodes]
+    # nodes_df = pd.DataFrame({'Node': nodes, 'Report': node_reports}).sort_values('Report', ascending=False).head(num_nodes)
+    # nodes_remove = list(set(nodes) - set(nodes_df['Node'].to_list()))
+    # [G.remove_nodes_from(nodes_remove)]
     
     #.groupby(['Teacher', 'Student']).sum()
     # if edges_split.shape[0] > num_nodes:
@@ -92,7 +91,7 @@ def network_visualizer(yaxis, city, fstyear,lastyr, num_nodes):
         row = edges[(edges['Teacher_ID'] == edge[0]) & (edges['Student_ID'] == edge[1])].iloc[0]
         source = row['Teacher_ID']
         target = row['Student_ID']
-        net.add_edge(int(source), int(target), color = value_to_hex(int(row[yaxis])), label = f"{row[yaxis]}")
+        net.add_edge(int(source), int(target), color = value_to_hex(int(row[yaxis])), label = f"{row[yaxis]}", value= int(row[yaxis]))
     
     # for _, row in edge_15.iterrows():
     #     source = row['Teacher']