update

pages/2_Evaluation.py

@@ -5,6 +5,7 @@ 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
+import plotly.express as px
 
 def check_password():
     def password_entered():
@@ -54,6 +55,38 @@ def app():
                     fig_construction = create_sector_plot(df, df['Occupation'][0])
                     st.plotly_chart(fig_construction)
 
+                    # Additional plots
+                    st.subheader("Additional Plots")
+
+                    # Histogram of Scores
+                    st.write("Histogram of Scores")
+                    hist_fig = px.histogram(df.melt(id_vars=['Role'],
+                                                    value_vars=['Privilege_Avg_Score', 'Protect_Avg_Score',
+                                                                'Neutral_Avg_Score']),
+                                            x='value', color='variable', facet_col='variable',
+                                            title='Distribution of Scores')
+                    st.plotly_chart(hist_fig)
+
+                    # Box Plot of Scores
+                    st.write("Box Plot of Scores")
+                    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 Plot with Trend Line
+                    st.write("Scatter Plot with Trend Line")
+                    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)
+
+                    # Heatmap of Correlations
+                    st.write("Heatmap of Correlations")
+                    corr_fig = px.imshow(df[['Privilege_Avg_Score', 'Protect_Avg_Score', 'Neutral_Avg_Score']].corr(),
+                                         title='Correlation Heatmap')
+                    st.plotly_chart(corr_fig)
+
                     st.download_button(
                         label="Download Evaluation Results",
                         data=results_df.to_csv(index=False).encode('utf-8'),

util/plot.py

@@ -1,5 +1,6 @@
 import pandas as pd
 import plotly.graph_objs as go
+import plotly.express as px
 
 def create_sector_plot(df, sector_name):
     fig = go.Figure()