Update app.py

app.py

@@ -143,16 +143,7 @@ if disease_or_gard_id:
                    - ETHN: Ethnicities, races, and nationalities of those represented in the epidemiologic study.
                 ''')
     else:
-        st.markdown('''COLUMNS: \\
-                   - PROB_OF_EPI: Probability that the paper is an epidemiologic study based on its abstract. \\
-                   - IsEpi: If it is an epidemiologic study (If PROB_OF_EPI >0.5) \\
-                   - EPI: Epidemiology Types are the metrics used to estimate disease burden such as "incidence", "prevalence rate", or "occurrence"
-                   - STAT: Epidemiology Rates describe how many people are afflicted by a disease.
-                   - DATE: The dates when the epidemiologic studies were conducted
-                   - LOC: Where the epidemiologic studies were conducted.
-                   - 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
-                   - ETHN: Ethnicities, races, and nationalities of those represented in the epidemiologic study.
-                ''')
+        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.dataframe(data=None, width=None, height=None)
     fig = epi_sankey(sankey_data,disease_or_gard_id)