Update app.py

app.py

@@ -1,7 +1,7 @@
 import nltk
-nltk.data.path.append("/home/user/app/nltk_data/")
-nltk.data.path.append("/home/user/app/nltk_data")
-nltk.data.path.append("home/user/app/nltk_data")
+#nltk.data.path.append("/home/user/app/nltk_data/")
+#nltk.data.path.append("/home/user/app/nltk_data")
+#nltk.data.path.append("home/user/app/nltk_data")
 nltk.data.path.append("home/user/app/nltk_data/")
 #nltk.download('stopwords')
 #nltk.download('punkt')
@@ -97,6 +97,7 @@ def epi_sankey(sankey_data, disease_or_gard_id):
           value = [relevant, gathered-relevant, epidemiologic, relevant-epidemiologic]
       ))])
     fig.update_layout(
+    hoverinfo ='none',
     hovermode = 'x',
     title="Search for the Epidemiology of "+disease_or_gard_id,
     font=dict(size = 10, color = 'black'),
@@ -121,6 +122,7 @@ if disease_or_gard_id:
                                 NER_pipeline, entity_classes,
                                 extract_diseases,GARD_dict, max_length,
                                 classify_model_vars)
+    df.replace(to_replace=None, value="None")
     st.dataframe(df, height=200)
     csv = convert_df(df)
     st.download_button(
@@ -129,6 +131,10 @@ if disease_or_gard_id:
         file_name=disease_or_gard_id+'.csv',
         mime='text/csv',
         )
+    
+    fig = epi_sankey(sankey_data,disease_or_gard_id)
+    st.plotly_chart(fig, use_container_width=True)
+    
     if 'IDS' in list(df.columns):
         st.markdown('''COLUMNS: \\
                    - PROB_OF_EPI: Probability that the paper is an epidemiologic study based on its abstract. \\
@@ -145,7 +151,4 @@ if disease_or_gard_id:
     else:
         st.subheader("Categories of Results")
         st.markdown("    - **PROB_OF_EPI**: Probability that the paper is an epidemiologic study based on its abstract.  \n  - **IsEpi**: If it is an epidemiologic study (If PROB_OF_EPI >0.5)  \n  - **EPI**: Epidemiology Types are the metrics used to estimate disease burden such as 'incidence', 'prevalence rate', or 'occurrence'  \n  - **STAT**: Epidemiology Rates describe how many people are afflicted by a disease.  \n  - **DATE**: The dates when the epidemiologic studies were conducted  \n  - **LOC**: Where the epidemiologic studies were conducted.  \n  - **SEX**: The biological sexes mentioned in the abstract. Useful for diseases that disproportionately affect one sex over the other or may provide context to composition of the study population  \n  - **ETHN**: Ethnicities, races, and nationalities of those represented in the epidemiologic study.")
-    #st.dataframe(data=None, width=None, height=None)
-    fig = epi_sankey(sankey_data,disease_or_gard_id)
-
-    st.plotly_chart(fig, use_container_width=True)
+    #st.dataframe(data=None, width=None, height=None)