Update src/streamlit_app.py

src/streamlit_app.py

@@ -20,7 +20,7 @@ st.markdown("""
         }
         /* Paragraph/write-up styling */
       .description {
-        max-width: 1200px;          /* prevent super long lines */
+        max-width: 1600px;          /* prevent super long lines */
         margin: 0 auto;            /* center the block */
         font-size: 18px;           /* comfortable reading size */
         line-height: 1.6;          /* good spacing */
@@ -149,4 +149,8 @@ fig.update_layout(
 )
 
 st.plotly_chart(fig, use_container_width=True)
-st.markdown("""<div class="description" The donut chart shows the share of the ten most frequent crime categories in the selected year. At the center, you can see that Vehicle ­– Stolen is the single largest slice, accounting for roughly 18.7% of all incidents, The remaining five categories each represent between 3%–5% of total incidents—these include miscellaneous crimes, criminal threats, assault with a deadly weapon, burglary, and minor vandalism. By displaying both slice size and percentage labels, the chart makes it easy to compare how dominant property‐related offenses are, versus violent or lesser‐common crimes, in that year’s LAPD data.</div>""",unsafe_allow_html=True)
+st.markdown("""<div class="description"> The donut chart shows the share of the ten most frequent crime categories in the selected year. 
+At the center, you can see that Vehicle ­– Stolen is the single largest slice, accounting for roughly 18.7% of all incidents, 
+The remaining five categories each represent between 3%–5% of total incidents—these include miscellaneous crimes, criminal threats, 
+assault with a deadly weapon, burglary, and minor vandalism. By displaying both slice size and percentage labels, the chart makes it easy 
+to compare how dominant property‐related offenses are, versus violent or lesser‐common crimes, in that year’s LAPD data.</div>""",unsafe_allow_html=True)