add new titles

.gitignore

@@ -0,0 +1,2 @@
+venv/
+.idea/

app.py

@@ -4,7 +4,7 @@
 
 
 import streamlit as st
-
+from streamlit.components.v1 import html
 from n4a_analytics_lib.analytics import (GlobalStatistics, IaaStatistics)
 
 
@@ -105,18 +105,19 @@ if option == "Inter-Annotator Agreement results":
         #tab1, tab2, tab3, tab4, tab5 = st.tabs(
         #    ["📈 IAA metrics", "🗃 IAA Metrics Legend", "✔️ Agree annotations", "❌ Disagree annotations",
         #     "🏷️ Global Labels Statistics"])
-        st.subheader("Fleiss Kappa (global score for group):")
-
+        st.markdown("## 📈 IAA metrics")
+        col1_kappa, col2_kappa = st.columns(2)
+        col1_kappa.subheader("Fleiss Kappa (global score for group):")
 
 
-        st.markdown(interpret_kappa(round(fleiss_kappa_function(matrix), 2)), unsafe_allow_html=True)
-        st.subheader("Cohen Kappa Annotators Matrix (score between annotators):")
+        col1_kappa.markdown(interpret_kappa(round(fleiss_kappa_function(matrix), 2)), unsafe_allow_html=True)
+        col1_kappa.subheader("Cohen Kappa Annotators Matrix (score between annotators):")
         # tab1.dataframe(df)
         data = []
         for coder_1, coder_2 in pairs:
             cohen_function = cohen_kappa_function(project_analyzed.labels_per_coder[coder_1], project_analyzed.labels_per_coder[coder_2])
             data.append(((coder_1, coder_2), cohen_function))
-            st.markdown(f"* {coder_1} <> {coder_2} : {interpret_kappa(cohen_function)}", unsafe_allow_html=True)
+            col1_kappa.markdown(f"* {coder_1} <> {coder_2} : {interpret_kappa(cohen_function)}", unsafe_allow_html=True)
             # print(f"* {coder_1} <> {coder_2} : {cohen_function}")
 
         intermediary = defaultdict(Counter)
@@ -138,7 +139,10 @@ if option == "Inter-Annotator Agreement results":
         sn.heatmap(df_cm, cmap=colors, annot=True, mask=mask, annot_kws={"size": 7}, vmin=0, vmax=1, ax=ax)  # font size
         # plt.show()
         st.pyplot(ax.figure)
-        st.markdown("""
+        col2_kappa.markdown("""
+        <div>
+        <div id="legend" style="right: 70em;">
+        <h3>🗃 IAA Metrics Legend</h3>
         <table>
         <thead>
         <tr>
@@ -193,10 +197,11 @@ if option == "Inter-Annotator Agreement results":
         agreement </td>
                       </tr>
                           </tbody>
-                              </table>"""
+                              </table></div></div>"""
 
         , unsafe_allow_html = True)
 
+
         ## commune
         @st.cache
         def convert_df(df_ex):
@@ -217,7 +222,7 @@ if option == "Inter-Annotator Agreement results":
 
         csv_agree = convert_df(df_agree)
 
-        st.subheader("Total agree annotations:")
+        st.subheader("✔️ Agree annotations")
         st.markdown(f"{total_unanime} / {len(df)} annotations ({round((total_unanime / len(df)) * 100, 2)} %)")
         st.download_button(
             "Press to Download CSV",
@@ -238,7 +243,7 @@ if option == "Inter-Annotator Agreement results":
         df_disagree = df[df[columns_to_compare].apply(lambda row: check_all_not_equal(row), axis=1)]
         total_desaccord = len(df_disagree)
         csv_disagree = convert_df(df_disagree)
-        st.subheader("Total disagree annotations:")
+        st.subheader("❌ Disagree annotations")
         st.markdown(
             f"{total_desaccord} / {len(df)} annotations ({round((total_desaccord / len(df)) * 100, 2)} %)")
         st.download_button(
@@ -299,6 +304,7 @@ if option == "Inter-Annotator Agreement results":
          return fig
 
         f = plot_pies(to_pie)
+        st.subheader("🏷️ Global Labels Statistics")
         st.pyplot(f.figure)
 
 # global project results view