Update appStore/vulnerability_analysis.py

appStore/vulnerability_analysis.py

@@ -91,72 +91,67 @@ def vulnerability_display():
 
     # Header
     st.subheader("Explore references to vulnerable groups:")
-    
-    col1, col2 = st.columns([1,1])
-    
-    with col1:
         
 
-        # Text 
-        num_paragraphs = len(df['Vulnerability Label'])
-        num_references = len(df_filtered['Group(s)'])
-       
-        st.markdown(f"""<div style="text-align: justify;"> The document contains a
-                total of <span style="color: red;">{num_paragraphs}</span> paragraphs.
-                We identified <span style="color: red;">{num_references}</span>
-                references to groups in vulnerable situations.</div>
-                <br>
-                In the chart on the right you can see how often each group has been referenced.
-                For a more detailed view in the text, see the paragraphs and 
-                their respective labels in the table below.</div>""", unsafe_allow_html=True)
-
-    with col2:
+    # Text 
+    num_paragraphs = len(df['Vulnerability Label'])
+    num_references = len(df_filtered['Group(s)'])
+   
+    st.markdown(f"""<div style="text-align: justify;"> The document contains a
+            total of <span style="color: red;">{num_paragraphs}</span> paragraphs.
+            We identified <span style="color: red;">{num_references}</span>
+            references to groups in vulnerable situations.</div>
+            <br>
+            In the chart on the right you can see how often each group has been referenced.
+            For a more detailed view in the text, see the paragraphs and 
+            their respective labels in the table below.</div>""", unsafe_allow_html=True)
+
         
-        ### Bar chart
-                    
-        # # Create a df that stores all the labels
-        df_labels = pd.DataFrame(list(label_dict.items()), columns=['Label ID', 'Label'])
+    ### Bar chart
+                
+    # # Create a df that stores all the labels
+    df_labels = pd.DataFrame(list(label_dict.items()), columns=['Label ID', 'Label'])
 
-        # Count how often each label appears in the "Group identified" column
-        group_counts = {}
+    # Count how often each label appears in the "Group identified" column
+    group_counts = {}
 
-        # Iterate through each sublist
-        for index, row in df_filtered.iterrows():
+    # Iterate through each sublist
+    for index, row in df_filtered.iterrows():
+        
+        # Iterate through each group in the sublist
+        for sublist in row['Group(s)']:
             
-            # Iterate through each group in the sublist
-            for sublist in row['Group(s)']:
-                
-                # Update the count in the dictionary
-                group_counts[sublist] = group_counts.get(sublist, 0) + 1
+            # Update the count in the dictionary
+            group_counts[sublist] = group_counts.get(sublist, 0) + 1
 
-        # Create a new dataframe from group_counts
-        df_label_count = pd.DataFrame(list(group_counts.items()), columns=['Label', 'Count'])
+    # Create a new dataframe from group_counts
+    df_label_count = pd.DataFrame(list(group_counts.items()), columns=['Label', 'Count'])
 
-        # Merge the label counts with the df_label DataFrame
-        df_label_count = df_labels.merge(df_label_count, on='Label', how='left')
+    # Merge the label counts with the df_label DataFrame
+    df_label_count = df_labels.merge(df_label_count, on='Label', how='left')
 
-        # Exclude the "Other" group
-        df_bar_chart = df_label_count[df_label_count['Label'] != 'Other']
-        
-        # Bar chart
-        fig = go.Figure()
-
-        fig.add_trace(go.Bar(
-            y=df_bar_chart.Label,
-            x=df_bar_chart.Count,
-            orientation='h', 
-            marker=dict(color='purple'),
-        ))
-        
-        # Customize layout
-        fig.update_layout(
-            title='Number of references to each group',
-            xaxis_title='Number of references',
-            yaxis_title='Group',
-        )
-
-        # Show the plot
-        #fig.show()
-
-        #Show plot
-        st.plotly_chart(fig, use_container_width=True) 
+    # Exclude the "Other" group
+    df_bar_chart = df_label_count[df_label_count['Label'] != 'Other']
+    
+    # Bar chart
+    fig = go.Figure()
+
+    fig.add_trace(go.Bar(
+        y=df_bar_chart.Label,
+        x=df_bar_chart.Count,
+        orientation='h', 
+        marker=dict(color='purple'),
+    ))
+    
+    # Customize layout
+    fig.update_layout(
+        title='Number of references to each group',
+        xaxis_title='Number of references',
+        yaxis_title='Group',
+    )
+
+    # Show the plot
+    #fig.show()
+
+    #Show plot
+    st.plotly_chart(fig, use_container_width=True)