Update app.py

app.py

@@ -22,11 +22,11 @@ file = st.file_uploader("", type=["csv"])
 if file is not None:
     # Read the CSV file into a Pandas DataFrame
     df = pd.read_csv(file)
-    st.markdown(f"<h3 style='color: #52565E; font-family: Verdana; font-size: 30px;'>{len(df)} reviews to analyse!</h3>", unsafe_allow_html=True)
+    st.markdown(f"<h5 style='font-family: Verdana;'>{len(df)-1} reviews to analyse!</h5>", unsafe_allow_html=True)
     
     # Write the total number of records
     st.markdown(
-        f'<div style="background-color: #4AA6DD; color: #ffffff; padding: 6px; font-size: 20px; font-family: Verdana; font-weight: bold; text-align: center; border-radius: 1rem;margin-top: 10px"> Distribution of Reviews </div>',
+        f'<div style="background-color: #4AA6DD; color: #ffffff; padding: 6px; font-size: 20px; font-family: Verdana; font-weight: bold; text-align: center; border-radius: 1rem;margin-top: 40px"> Distribution of Reviews </div>',
         unsafe_allow_html=True
     )
 
@@ -75,31 +75,33 @@ if file is not None:
         df = df[df['sentiment'] == filter_sentiment]
     
     # Set the max number of rows to display at a time
-    max_rows = 10
+    max_rows = 15
     
     # Create HTML table with no border and centered text
     table_html = (df.style
-                  .set_properties(**{'text-align': 'left','font-size': '15px','font-family': 'Verdana','margin-bottom':'60px'})
+                  .set_properties(**{'text-align': 'left','font-size': '15px','font-family': 'Verdana'})
                   .set_table_styles([{'selector': 'th', 'props': [('border', '0px')]},
                                      {'selector': 'td', 'props': [('border', '0px')]}])
+                  .set_table_attributes('style="position: sticky; top: 0;"')
                   .to_html(index=False, escape=False))
     
     # Wrap the table inside a div with a fixed height and scrollable content
     st.write(f'<div style="height: {max_rows*30}px; overflow-y: scroll;">{table_html}</div>', unsafe_allow_html=True)
 
-
-
     def convert_df(df):
         # IMPORTANT: Cache the conversion to prevent computation on every rerun
         return df.to_csv().encode('utf-8')
     
     csv = convert_df(df)
     
+    # Add some space between the download button and the table
+    st.write("<br>", unsafe_allow_html=True)
+    
     st.download_button(
         label="Download data as CSV",
         data=csv,
-        file_name='Review Sentiments.csv'
+        file_name='Review Sentiments.csv',
+        style="margin-top: 40px;"
     )
-
 else:
     st.write("Please upload a CSV file.")