Upload app.py

app.py

@@ -16,7 +16,6 @@ import plotly.graph_objects as go
 import os
 
 GROQ_API_KEY = os.environ.get("GROQ_TOKENS")
-
 st.set_page_config(layout="wide")
 
 # Custom style CSS
@@ -1175,44 +1174,105 @@ with col2a:  # Sidebar untuk chatbot
                     print("\\nHasil analisis:")
                     print(result)
                     
-                - Untuk visualisasi WAJIB gunakan Plotly dengan template:
-                    import plotly.express as px
+                - Untuk visualisasi WAJIB gunakan Plotly dengan contoh template:
                     # JANGAN gunakan fig.show() atau renderer apapun
-                    # Contoh bar chart
-                    fig = px.bar(
-                        df,
-                        x='col1',
-                        y='col2',
-                        title='Judul Chart',
-                        color='col3',
-                        template='plotly_dark'
+                    Contoh untuk histogram:
+                    fig = px.histogram(
+                        df_temp,
+                        x=column_name,
+                        opacity=0.7,
+                        color_discrete_sequence=["#00CC96"],
                     )
+
+                    fig.update_traces(marker_line_color='black', marker_line_width=1)
+
                     fig.update_layout(
-                        xaxis_title='Label X',
-                        yaxis_title='Label Y',
-                        hovermode='x unified'
+                        template='seaborn',
+                        title=f"Histogram of {{column_name}}",
+                        xaxis_title=column_name,
+                        yaxis_title="Count",
+                        bargap=0.1
+                        )
                     )
-                    fig.show()
+                    
+                    - Berikut adalah contoh bar chart namun pastikan dulu unique value yang akan diplot kurang dari 100                   
+                    top_10_customers['Customer_ID'] = top_10_customers['Customer_ID'].astype(str)
+                    # selalu cek dulu jumlah unique value data
+                    if top_10_customers['Customer_ID'].unique() < 100:
+                        # Plot bar chart
+                        fig = px.bar(
+                            top_10_customers,
+                            x='Customer_ID',
+                            y='CLV',
+                            color='CLV',
+                            template='plotly_dark',
+                            title='Top 10 Customers by CLV',
+                            category_orders={{"Customer_ID": top_10_customers['Customer_ID'].tolist()}}
+                        )
+
+                        # Pastikan sumbu X bertipe kategori (bukan numeric)
+                        fig.update_xaxes(type='category')
+
+                        fig.update_layout(
+                            bargap=0.1,
+                            xaxis_title='Customer ID',
+                            yaxis_title='CLV',
+                            hovermode='x unified'
+                        )
+                    
+                    Jika if top_10_customers['Customer_ID'].unique() > 100 maka buat bar chart seperti biasa, perinta ini tidak berlaku untuk chart lain seperti pie chart
+
                     
                     # Contoh scatter plot
                     fig = px.scatter(
                         df,
                         x='col1',
                         y='col2',
-                        size='col3',
                         color='col4',
                         trendline='ols'
                     )
                     
                     # Contoh pie chart
+                    # Tentukan pull untuk bagian terbesar agar sedikit terpisah
+                    feedback_counts = df[feedback_col].value_counts().reset_index()
+                    feedback_counts.columns = [feedback_col, 'count']
+
+                    # Print feedback counts
+                    print("\nFeedback counts:")
+                    print(feedback_counts)
+
+                    # Create pie chart for feedback
                     fig = px.pie(
-                        df,
-                        names='col_category',
-                        values='col_value',
-                        hole=0.3
+                        feedback_counts,
+                        names=feedback_col,
+                        values='count',
+                        hole=0.3,
+                        title='Feedback Distribution'
+                    )
+
+                    # Determine the largest segment to pull out
+                    max_segment = feedback_counts[feedback_counts['count'] == feedback_counts['count'].max()][feedback_col].values[0]
+                    pull = [0.2 if feedback == max_segment else 0 for feedback in feedback_counts[feedback_col]]
+
+                    # Update traces for pulling out the largest segment
+                    fig.update_traces(
+                        pull=pull
                     )
+
+                    # Update layout for better visualization
+                    fig.update_layout(
+                        margin=dict(t=50, b=50, l=50, r=50),
+                        title_x=0.5
+                    )
+
+                    # Add border to the chart
+                    fig.update_xaxes(showline=True, linewidth=1, linecolor='black', mirror=True)
+                    fig.update_yaxes(showline=True, linewidth=1, linecolor='black', mirror=True)
+
+                    fig.show()
+
                     - Selalu gunakan border untuk chart
-                    - Gunakan bargap 0.1 untuk bar chart
+                    - Jangan gunakan fig.show()
                     - Simpan objek figure sebagai variabel