merge

data_measurements/streamlit_utils.py

@@ -390,7 +390,7 @@ def expander_zipf(z, zipf_fig, column_id):
             if z.xmin > 5:
                 st.markdown(xmin_warning)
         except:
-            st.write("Under construction!")
+            st.write("Under construction! 😱 🚧")
 
 
 ### Finally finally finally, show nPMI stuff.
@@ -404,31 +404,34 @@ def npmi_widget(npmi_stats, min_vocab, column_id):
     :return:
     """
     with st.expander(f"Word Association{column_id}: nPMI", expanded=False):
-        if len(npmi_stats.available_terms) > 0:
-            expander_npmi_description(min_vocab)
-            st.markdown("-----")
-            term1 = st.selectbox(
-                f"What is the first term you want to select?{column_id}",
-                npmi_stats.available_terms,
-            )
-            term2 = st.selectbox(
-                f"What is the second term you want to select?{column_id}",
-                reversed(npmi_stats.available_terms),
-            )
-            # We calculate/grab nPMI data based on a canonical (alphabetic)
-            # subgroup ordering.
-            subgroup_pair = sorted([term1, term2])
-            try:
-                joint_npmi_df = npmi_stats.load_or_prepare_joint_npmi(subgroup_pair)
-                npmi_show(joint_npmi_df)
-            except KeyError:
+        try:
+            if len(npmi_stats.available_terms) > 0:
+                expander_npmi_description(min_vocab)
+                st.markdown("-----")
+                term1 = st.selectbox(
+                    f"What is the first term you want to select?{column_id}",
+                    npmi_stats.available_terms,
+                )
+                term2 = st.selectbox(
+                    f"What is the second term you want to select?{column_id}",
+                    reversed(npmi_stats.available_terms),
+                )
+                # We calculate/grab nPMI data based on a canonical (alphabetic)
+                # subgroup ordering.
+                subgroup_pair = sorted([term1, term2])
+                try:
+                    joint_npmi_df = npmi_stats.load_or_prepare_joint_npmi(subgroup_pair)
+                    npmi_show(joint_npmi_df)
+                except KeyError:
+                    st.markdown(
+                        "**WARNING!** The nPMI for these terms has not been pre-computed, please re-run caching."
+                    )
+            else:
                 st.markdown(
-                    "**WARNING!** The nPMI for these terms has not been pre-computed, please re-run caching."
+                    "No words found co-occurring with both of the selected identity terms."
                 )
-        else:
-            st.markdown(
-                "No words found co-occurring with both of the selected identity terms."
-            )
+        except:
+            st.write("Under construction! 😱 🚧")
 
 
 def npmi_show(paired_results):