sort based on the color codes then iso code.

app.py

@@ -17,20 +17,19 @@ def render_home_table():
     df_data = pd.DataFrame(data).transpose()
     df_data['ISO Code'] = df_data.index
 
-    # Sort by ISO Code
-    df_data = df_data.sort_values(by='ISO Code')
-
     df_data['Number of Sites'] = df_data['Number of Sites'].astype(str)  # Convert to string
     df_data['ISO Code'] = df_data['ISO Code'].astype(str)  # Convert to string
     df_data['Number of Sites'] = df_data.apply(lambda row: '<a href="/?isocode={}&site=True" target="_self">{}</a>'.format(row['ISO Code'], row['Number of Sites']), axis=1)
     df_data['Number of Links'] = df_data.apply(lambda row: '<a href="/?isocode={}&links=True" target="_self">{}</a>'.format(row['ISO Code'], row['Number of Links']), axis=1)
-    df_data["Supported by MADLAD400 & FLORES & GLOT500"] = df_data.apply(lambda row: color_mapping([row["Supported by allenai/MADLAD-400"] + row["Supported by facebook/flores"] +  row["Supported by cis-lmu/Glot500"]]), axis =1)
+    df_data["Supported by MADLAD400, FLORES200, GLOT500"] = df_data.apply(lambda row: color_mapping([row["Supported by allenai/MADLAD-400"] + row["Supported by facebook/flores"] +  row["Supported by cis-lmu/Glot500"]]), axis =1)
+    df_data['Color_Order'] = pd.Categorical(df_data['Supported by MADLAD400, FLORES200, GLOT500'], categories=['🟥', '🟧', '🟨', '🟩'], ordered=True)
+    # Sort by Color_Order then ISO Code
+    df_data = df_data.sort_values(by=['Color_Order', 'ISO Code'])
 
     # Display the table
-    df_data = df_data[['ISO Code', 'Language Name', 'Family', 'Subgrouping', 'Number of Sites', 'Number of Links', 'Number of Speakers', 'Supported by MADLAD400 & FLORES & GLOT500']]
+    df_data = df_data[['ISO Code', 'Language Name', 'Family', 'Subgrouping', 'Number of Sites', 'Number of Links', 'Number of Speakers', 'Supported by MADLAD400, FLORES200, GLOT500']]
     st.write(df_to_html(df_data), unsafe_allow_html=True)
 
-
 @st.cache_data
 def render_site_table(isocode):