Update app.py

app.py

@@ -143,7 +143,8 @@ if disease_or_gard_id:
                    - ETHN: Ethnicities, races, and nationalities of those represented in the epidemiologic study.
                 ''')
     else:
-        st.markdown("COLUMNS:  \n  - 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.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)