Handling for no words

data_measurements/streamlit_utils.py

@@ -111,30 +111,33 @@ def expander_general_stats(dstats, column_id):
             "Use this widget to check whether the terms you see most represented"
             " in the dataset make sense for the goals of the dataset."
         )
-        st.markdown("There are {0} total words".format(str(dstats.total_words)))
-        st.markdown(
-            "There are {0} words after removing closed "
-            "class words".format(str(dstats.total_open_words))
-        )
-        st.markdown(
-            "The most common "
-            "[open class words](https://dictionary.apa.org/open-class-words) "
-            "and their counts are: "
-        )
-        st.dataframe(dstats.sorted_top_vocab_df)
-        st.markdown(
-            "There are {0} missing values in the dataset.".format(
-                str(dstats.text_nan_count)
+        if dstats.total_words == 0:
+            st.markdown("Eh oh...not finding the file I need. 😭  Probably it will be there soon. 🤞 Check back later!")
+        else:
+            st.markdown("There are {0} total words".format(str(dstats.total_words)))
+            st.markdown(
+                "There are {0} words after removing closed "
+                "class words".format(str(dstats.total_open_words))
             )
-        )
-        if dstats.dedup_total > 0:
             st.markdown(
-                "There are {0} duplicate items in the dataset. "
-                "For more information about the duplicates, "
-                "click the 'Duplicates' tab below.".format(str(dstats.dedup_total))
+                "The most common "
+                "[open class words](https://dictionary.apa.org/open-class-words) "
+                "and their counts are: "
             )
-        else:
-            st.markdown("There are 0 duplicate items in the dataset. ")
+            st.dataframe(dstats.sorted_top_vocab_df)
+            st.markdown(
+                "There are {0} missing values in the dataset.".format(
+                    str(dstats.text_nan_count)
+                )
+            )
+            if dstats.dedup_total > 0:
+                st.markdown(
+                    "There are {0} duplicate items in the dataset. "
+                    "For more information about the duplicates, "
+                    "click the 'Duplicates' tab below.".format(str(dstats.dedup_total))
+                )
+            else:
+                st.markdown("There are 0 duplicate items in the dataset. ")
 
 
 ### Show the label distribution from the datasets