fix errors

common.py

@@ -104,16 +104,6 @@ def dedup_pairs_bands():
         }
     ).to_html(index=False, border=0)
 
-# Get the HTML table
-table_html_data = dedup_pairs_bands()
-
-# Wrap the table in a Div for styling
-table_div_data = Div(
-    text=table_html_data,
-    style="display: flex; justify-content: center; align-items: center; width: 100%; max-width: 100%; height: auto; overflow-x: auto;"
-)
-
-
 def dup_docs_count_graph():
     dup_docs_count = {
         "80": 382164413,
@@ -288,7 +278,7 @@ pii_table = pd.DataFrame(
 )
 
 table_html_pii = pii_table.to_html(index=False, border=0)
-table_div_pii = Div(NotStr(table_html_pii), style="margin: 40px;")
+table_div_pii = Div(NotStr(table_html_pii), style="display: flex; justify-content: center; align-items: center; width: 100%; max-width: 100%; height: auto; overflow-x: auto;")
 
 global_div = Div(
     Section(
@@ -374,7 +364,7 @@ global_div = Div(
         P(
             "There is a high chance that duplicates from different bands will have the same pairs in the same horizontal partition. Performing the Bloom filter step reduces the number of pairs by nearly ninefold."
         ),
-        Div(NotStr(dedup_pairs_bands()), style="margin: 40px;"),
+        Div(NotStr(dedup_pairs_bands()), style="display: flex; justify-content: center; align-items: center; width: 100%; max-width: 100%; height: auto; overflow-x: auto;"),
         P(
             "The resulting unique pairs are then used to identify clusters of near-duplicates by finding connected components in a graph, where the vertices represent documents and the edges represent matches."
         ),