Update app.py

app.py

@@ -25,34 +25,14 @@ df.dropna(subset=['License Type', 'License Status', 'Original Issue Date'], inpl
 df['Original Issue Year'] = df['Original Issue Date'].dt.year
 
 # Visualization 1: Bar chart of licenses by Status
-# st.subheader("Licenses by Status")
-# category_counts = df['License Status'].value_counts().reset_index()
-# category_counts.columns = ['License Status', 'Count']
-
-# if not category_counts.empty:
-#     chart1 = alt.Chart(category_counts).mark_bar().encode(
-#         x=alt.X('License Status', sort='-y', title='License Type'),
-#         y=alt.Y('Count', title='Number of Licenses'),
-#         color=alt.Color('License Status', legend=None)
-#     ).properties(
-#         width=600,
-#         height=400,
-#         title="Number of Licenses by Status"
-#     )
-#     st.altair_chart(chart1)
-# else:
-#     st.write("No data available for the 'License Status' plot.")
-
 st.subheader("Licenses by Status")
 category_counts = df['License Status'].value_counts().reset_index()
 category_counts.columns = ['License Status', 'Count']
 
 if not category_counts.empty:
-    # Set Y-axis domain with 10% padding above the max count if below 100, else dynamic
-    y_max = min(100, category_counts['Count'].max() * 1.1)
     chart1 = alt.Chart(category_counts).mark_bar().encode(
         x=alt.X('License Status', sort='-y', title='License Type'),
-        y=alt.Y('Count', title='Number of Licenses', scale=alt.Scale(domain=[0, y_max])),
+        y=alt.Y('Count', title='Number of Licenses'),
         color=alt.Color('License Status', legend=None)
     ).properties(
         width=600,
@@ -63,7 +43,6 @@ if not category_counts.empty:
 else:
     st.write("No data available for the 'License Status' plot.")
 
-
 # Write-up for Visualization 1
 st.write("""
 **Licenses by Status**: This visualization highlights the distribution of licenses across different statuses.