update

pages/2_Evaluation.py

@@ -4,6 +4,7 @@ import streamlit as st
 import pandas as pd
 from io import StringIO
 from util.evaluation import statistical_tests,calculate_correlations,calculate_divergences
+from util.plot import create_sector_plot
 
 def check_password():
     def password_entered():
@@ -50,6 +51,10 @@ def app():
 
                     st.write('Combined Results:', results_df)
 
+                    st.subheader("Construction Sector Scores")
+                    fig_construction = create_sector_plot(df, df['Occupation'][0])
+                    st.plotly_chart(fig_construction)
+
                     st.download_button(
                         label="Download Evaluation Results",
                         data=results_df.to_csv(index=False).encode('utf-8'),

util/plot.py

@@ -0,0 +1,33 @@
+import pandas as pd
+import plotly.graph_objs as go
+
+def create_sector_plot(df, sector_name):
+    fig = go.Figure()
+
+    fig.add_trace(go.Scatter(
+        x=df.index, y=df['Privilege_Avg_Score'],
+        mode='lines+markers', name='Privilege (Male Info)',
+        text=df['Role'], hoverinfo='text+y'
+    ))
+
+    fig.add_trace(go.Scatter(
+        x=df.index, y=df['Protect_Avg_Score'],
+        mode='lines+markers', name='Protection (Female Info)',
+        text=df['Role'], hoverinfo='text+y'
+    ))
+
+    fig.add_trace(go.Scatter(
+        x=df.index, y=df['Neutral_Avg_Score'],
+        mode='lines+markers', name='Neutral (No Gender Info)',
+        text=df['Role'], hoverinfo='text+y'
+    ))
+
+    fig.update_layout(
+        title=f'{sector_name} Sector Scores',
+        xaxis_title='Resume Index',
+        yaxis_title='Score',
+        legend_title='Score Type',
+        hovermode='closest'
+    )
+
+    return fig