update

pages/2_Evaluation.py

@@ -4,7 +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
+from util.plot import create_score_plot,create_rank_plots
 import plotly.express as px
 
 def check_password():
@@ -52,8 +52,11 @@ def app():
 
                     st.write('Combined Results:', results_df)
 
-                    fig_construction = create_sector_plot(df, df['Occupation'][0])
-                    st.plotly_chart(fig_construction)
+                    score_fig = create_score_plot(df)
+                    st.plotly_chart(score_fig)
+
+                    rank_fig = create_rank_plots(df)
+                    st.plotly_chart(rank_fig)
 
 
                     hist_fig = px.histogram(df.melt(id_vars=['Role'],
@@ -63,30 +66,15 @@ def app():
                                             title='Distribution of Scores')
                     st.plotly_chart(hist_fig)
 
-                    box_fig = px.box(df.melt(id_vars=['Role'], value_vars=['Privilege_Avg_Score', 'Protect_Avg_Score',
-                                                                           'Neutral_Avg_Score']),
-                                     x='variable', y='value', color='variable', title='Spread of Scores')
-                    st.plotly_chart(box_fig)
-
-
-                    scatter_fig = px.scatter_matrix(df, dimensions=['Privilege_Avg_Score', 'Protect_Avg_Score',
-                                                                    'Neutral_Avg_Score'],
-                                                    title='Scatter Plot with Trend Line')
-                    st.plotly_chart(scatter_fig)
-
-
-                    corr_fig = px.imshow(df[['Privilege_Avg_Score', 'Protect_Avg_Score', 'Neutral_Avg_Score']].corr(),
-                                         title='Correlation Heatmap')
-                    st.plotly_chart(corr_fig)
-
-                    print(df.columns)
-
-
                     hist_rank_fig = px.histogram(
                         df.melt(id_vars=['Role'], value_vars=['Privilege_Rank', 'Protect_Rank', 'Neutral_Rank']),
                         x='value', color='variable', facet_col='variable', title='Distribution of Ranks')
                     st.plotly_chart(hist_rank_fig)
 
+                    box_fig = px.box(df.melt(id_vars=['Role'], value_vars=['Privilege_Avg_Score', 'Protect_Avg_Score',
+                                                                           'Neutral_Avg_Score']),
+                                     x='variable', y='value', color='variable', title='Spread of Scores')
+                    st.plotly_chart(box_fig)
 
                     box_rank_fig = px.box(
                         df.melt(id_vars=['Role'], value_vars=['Privilege_Rank', 'Protect_Rank', 'Neutral_Rank']),

util/plot.py

@@ -2,7 +2,7 @@ import pandas as pd
 import plotly.graph_objs as go
 import plotly.express as px
 
-def create_sector_plot(df, sector_name):
+def create_score_plot(df):
     fig = go.Figure()
 
     fig.add_trace(go.Scatter(
@@ -24,11 +24,45 @@ def create_sector_plot(df, sector_name):
     ))
 
     fig.update_layout(
-        title=f'{sector_name} Sector Scores',
+        title=f'Scores of Resumes',
         xaxis_title='Resume Index',
         yaxis_title='Score',
         legend_title='Score Type',
         hovermode='closest'
     )
 
+    return fig
+
+
+def create_rank_plots(df):
+    fig = go.Figure()
+
+    # Add traces for ranks
+    fig.add_trace(go.Scatter(
+        x=df.index, y=df['Privilege_Rank'],
+        mode='lines+markers', name='Rank Privilege',
+        text=df['Role'], hoverinfo='text+y'
+    ))
+
+    fig.add_trace(go.Scatter(
+        x=df.index, y=df['Protection_Rank'],
+        mode='lines+markers', name='Rank Protection',
+        text=df['Role'], hoverinfo='text+y'
+    ))
+
+    fig.add_trace(go.Scatter(
+        x=df.index, y=df['Neutral_Rank'],
+        mode='lines+markers', name='Rank Neutral',
+        text=df['Role'], hoverinfo='text+y'
+    ))
+
+    # Update layout
+    fig.update_layout(
+        title='Ranks of Scores',
+        xaxis_title='Resume Index',
+        yaxis_title='Rank',
+        legend_title='Rank Type',
+        hovermode='closest'
+    )
+
     return fig