minor fixes

app.py

@@ -82,7 +82,7 @@ def get_user_info():
     gender_value = gender_options.index(gender_input)
 
     expert_options = [
-        '[PLEASE SELECT]', 
+        '[Please select]', 
         'No, I do not have a background in social or behavioral sciences', 
         'Yes, I have either studied social or behavioral sciences or I am currently a student in this field', 
         'Yes, I have either worked as a researcher in the field of social or behavioral sciences or I have had past experience as a researcher in this area'
@@ -261,7 +261,9 @@ def show_data(placeholder):
             st.divider()   
             st.markdown("""
                 ## Explore the data
-                Figures show the accuarcy in precitions of human-rated item desirability by the sentiment model (left) and the desirability model (right), using `test`-partition data only.
+                Figures show the accuarcy in precitions of human-rated item desirability by 
+                the sentiment model (left) and the desirability model (right), using 
+                `test`-partition data only. 
             """)
 
             show_covariates = st.checkbox('Show covariates', value=True)
@@ -270,19 +272,22 @@ def show_data(placeholder):
             else:
                 option = None
             
-            if 'df' in st.session_state:
-                plot = plots.scatter_plot(st.session_state.df, option)
-                st.plotly_chart(plot, theme=None, use_container_width=True)
+            if 'df' not in st.session_state:
+                utils.load_data()
+
+            plot = plots.scatter_plot(st.session_state.df, option)
+            st.plotly_chart(plot, theme=None, use_container_width=True)
 
 def main():
     st.markdown("""
         # Machine-Based Item Desirability Ratings
-        This web application demonstrates how item desirability ratings can be obtained with natural language processing ("AI") and accompanies the paper "*Expanding the Methodological Toolbox: Machine-Based Item Desirability Ratings as an Alternative to Human-Based Ratings*".
+        This web application demonstrates how item desirability ratings can be obtained with natural language processing ("AI"), and accompanying the paper "*Expanding the Methodological Toolbox: Machine-Based Item Desirability Ratings as an Alternative to Human-Based Ratings*".
         
         *Hommel, B. E. (2023). Expanding the methodological toolbox: Machine-based item desirability ratings as an alternative to human-based ratings. Personality and Individual Differences, 213, 112307. https://doi.org/10.1016/j.paid.2023.112307*
 
         <small>https://www.magnolia-psychometrics.com/</small>
     """, unsafe_allow_html=True)
+
     placeholder_launch = st.empty()
     placeholder_summary = st.empty()
     placeholder_demo = st.empty()

utils.py

@@ -12,7 +12,7 @@ id_vars = [
     'rater_group', 'study', 'instrument'
 ]
 
-if 'df' not in st.session_state:
+def load_data():
     st.session_state.df = (
         pd
         .read_feather(path='data.feather')