Update app.py

app.py

@@ -103,20 +103,21 @@ if 'key0' in st.session_state:
     
     if topic == 'Vulnerability':
 
-        # Assign dataframe easier name 
+        # Assign dataframe a name
         df_vul = st.session_state['key0']
         
         # Header
-        st.subheader("Explore here which references to vulnerable groups were identified:")
+        st.subheader("Explore the references to vulnerable groups:")
 
         # Text 
         num_paragraphs = len(df_vul['Vulnerability Label'])
-        num_references = df_vul[df_vul['Vulnerability Label'] != 'Other']
+        num_references = len(df_vul[df_vul['Vulnerability Label'] != 'Other'])
         
         st.markdown(f"""<div style="text-align: justify;"> The document has a
                 total of <span style="color: red;">{num_paragraphs}</span> paragraphs.
                 In total, we found <span style="color: red;">{num_references}</span>
-                to vulnerable groups.</div>""", unsafe_allow_html=True)
+                paragraphs that contain a reference to a vulnerable group.
+                </div>""", unsafe_allow_html=True)
     
            
         ### Pie chart
@@ -125,7 +126,7 @@ if 'key0' in st.session_state:
         df_labels = pd.DataFrame(list(label_dict.items()), columns=['Label ID', 'Label'])
 
         # Count how often each label appears in the "Vulnerability Labels" column
-        label_counts = st.session_state['key0']['Vulnerability Label'].value_counts().reset_index()
+        label_counts = df_vul['Vulnerability Label'].value_counts().reset_index()
         label_counts.columns = ['Label', 'Count']
 
         # Merge the label counts with the df_label DataFrame
@@ -144,7 +145,7 @@ if 'key0' in st.session_state:
         st.plotly_chart(fig, use_container_width=True)
     
         ### Table 
-        st.table(st.session_state['key0'])
+        st.table(df_vul[df_vul['Vulnerability Label'] != 'Other'])
 
        # vulnerability_analysis.vulnerability_display()
     # elif topic == 'Action':