Update app.py

app.py

@@ -72,7 +72,7 @@ st.sidebar.header("Dashboard Controls")
 
 # First, define the visualization type (viz_type) selection
 viz_type = st.sidebar.selectbox("Select Visualization", [
-    "Complaint Types", "Geographic Distribution", "Complaints by Disposition", "Monthly Trends by Complaint Type",
+    "Complaint Types", "Geographic Distribution", "Complaints by Disposition", "Submission Methods","Monthly Trends by Complaint Type",
     "Complaints Over Time", "Complaints by Housing Block and Type"
 ])
 
@@ -124,8 +124,6 @@ if viz_type == "Complaints by Housing Block and Type" and selected_block != 'All
 st.header(f"Analysis for {'All Time' if selected_year == 'All Time' else selected_year}")
 
 
-
-
 # Display metrics
 col1, col2 = st.columns(2)
 with col1:
@@ -214,21 +212,50 @@ elif viz_type == "Geographic Distribution":
 #     """)
 
 
-# elif viz_type == "Submission Methods":
-#     st.subheader("Submission Methods Analysis")
-#     submission_counts = filtered_data['Method Submitted'].value_counts()
-#     fig, ax = plt.subplots(figsize=(10, 6))
-#     sns.barplot(x=submission_counts.values, y=submission_counts.index, palette='inferno', ax=ax)
-#     st.pyplot(fig)
+# Submission Methods Analysis
+elif viz_type == "Submission Methods":
+    st.subheader("Submission Methods Analysis")
+
+    # Allow the user to select the type of chart (Bar or Pie)
+    plot_type = st.selectbox("Select Plot Type", options=["Bar Chart", "Pie Chart"])
+
+    # Get the top 5 submission methods
+    submission_counts = filtered_data['Method Submitted'].value_counts().nlargest(5)
+    submission_data = submission_counts.reset_index()
+    submission_data.columns = ['Submission Method', 'Count']
+
+    if plot_type == "Bar Chart":
+        # Create a bar chart with Seaborn
+        fig, ax = plt.subplots(figsize=(10, 6))
+        sns.barplot(x=submission_data['Count'], y=submission_data['Submission Method'], palette='inferno', ax=ax)
+        st.pyplot(fig)
+    
+    elif plot_type == "Pie Chart":
+        # Create an interactive pie chart with Plotly
+        fig = px.pie(
+            submission_data,
+            names='Submission Method',
+            values='Count',
+            title="Top 5 Submission Methods Distribution",
+            color_discrete_sequence=px.colors.inferno,
+            labels={"Count": "Number of Complaints", "Submission Method": "Method Submitted"},
+            hover_data=['Count']
+        )
+        fig.update_traces(textinfo='percent+label', hovertemplate='<b>%{label}</b><br>Complaints: %{value}<br>Percentage: %{percent}')
+        st.plotly_chart(fig, use_container_width=True)
+
+    # Updated write-up
+    st.write("""
+    **What this visualization shows:**  
+    This chart shows the number of complaints submitted via different methods, such as email, phone, online form, etc., with a focus on the top 5 submission methods.
+    
+    **Why it's interesting:**  
+    By analyzing submission methods, we can understand how users prefer to submit complaints. This insight helps in focusing efforts on improving the most used channels, ensuring better user engagement.
+    
+    **Color Scheme:**  
+    The 'inferno' color palette highlights differences in submission frequency, with darker shades representing higher submission counts.
+    """)
 
-#     st.write("""
-#     **What this visualization shows:**  
-#     This bar chart shows the number of complaints submitted via different methods, such as email, phone, online form, etc.  
-#     **Why it's interesting:**  
-#     By analyzing submission methods, we can understand how users prefer to submit complaints and focus on improving the most used channels.  
-#     **Color Scheme:**  
-#     The 'inferno' color palette is used to highlight differences in submission frequency, with darker shades indicating higher submission counts.  
-#     """)
 
 
 # elif viz_type == "Complaints by Disposition":