Upload 3 files

app_diabetes.py

@@ -0,0 +1,99 @@
+# ---ADVANCED INTERACTIVE DASHBOARD (REAL DATA) ---
+import gradio as gr
+import plotly.express as px
+import pandas as pd
+
+# Load ulang data untuk memastikan aman di fungsi Gradio
+df = pd.read_csv('diabetes_dataset.csv')
+df['Diabetes_Label'] = df['diabetes'].map({0: 'Negative', 1: 'Positive'})
+
+def update_dashboard(age_start, age_end, selected_smoking, selected_gender):
+    # 1. Filter Data (Aman & Anti-Error)
+    if age_start > age_end:
+        age_start, age_end = age_end, age_start
+
+    if not selected_smoking:
+        selected_smoking = df['smoking_history'].unique().tolist()
+
+    if not selected_gender:
+        selected_gender = df['gender'].unique().tolist()
+
+    filtered_df = df[(df['age'] >= age_start) &
+                     (df['age'] <= age_end) &
+                     (df['smoking_history'].isin(selected_smoking)) &
+                     (df['gender'].isin(selected_gender))]
+
+    # Handle jika data kosong setelah difilter
+    if filtered_df.empty:
+        empty_fig = px.scatter(title="⚠️ Tidak ada data pasien dengan kriteria ini.")
+        return empty_fig, empty_fig, empty_fig, "### ⚠️ Data Kosong. Silakan ubah filter."
+
+    # 2. GRAFIK 1: SCATTER PLOT INTERAKTIF
+    fig_scatter = px.scatter(filtered_df, x='hbA1c_level', y='blood_glucose_level',
+                             color='Diabetes_Label', size='bmi', hover_data=['age', 'gender'],
+                             color_discrete_map={'Negative': '#636EFA', 'Positive': '#EF553B'},
+                             title=f"🩺 Indikator Klinis (Usia {age_start} - {age_end})",
+                             template="plotly_white")
+    fig_scatter.add_vline(x=6.5, line_dash="dash", line_color="red", annotation_text="Batas HbA1c")
+
+    # 3. GRAFIK 2: PIE CHART (Rasio Diabetes)
+    diabetes_counts = filtered_df['Diabetes_Label'].value_counts().reset_index()
+    diabetes_counts.columns = ['Status', 'Count']
+    fig_pie = px.pie(diabetes_counts, values='Count', names='Status',
+                     color='Status', color_discrete_map={'Negative': '#636EFA', 'Positive': '#EF553B'},
+                     title="📊 Rasio Positif vs Negatif", hole=0.4, template="plotly_white")
+
+    # 4. GRAFIK 3: HISTOGRAM (Distribusi BMI)
+    fig_hist = px.histogram(filtered_df, x='bmi', color='Diabetes_Label',
+                            barmode='overlay', title="👥 Distribusi Obesitas (BMI)",
+                            color_discrete_map={'Negative': '#636EFA', 'Positive': '#EF553B'},
+                            template="plotly_white")
+
+    # 5. RINGKASAN EKSEKUTIF
+    total_patients = len(filtered_df)
+    positive_cases = len(filtered_df[filtered_df['diabetes'] == 1])
+    prevalence = (positive_cases / total_patients) * 100 if total_patients > 0 else 0
+
+    summary = f"""
+    ### 📋 Executive Summary
+    * **Populasi Terfilter:** **{total_patients:,}** pasien
+    * **Kasus Positif:** **{positive_cases:,}** pasien
+    * **Prevalensi Risiko:** **{prevalence:.1f}%**
+    """
+
+    return fig_scatter, fig_pie, fig_hist, summary
+
+# --- UI GRADIO ---
+with gr.Blocks(title="Diabetes Risk Dashboard") as app:
+    gr.Markdown("# 🩸 Advanced Diabetes Risk Analytics")
+    gr.Markdown("Eksplorasi profil pasien menggunakan dataset riil untuk mengidentifikasi korelasi medis.")
+
+    with gr.Row():
+        with gr.Column(scale=2):
+            in_smoking = gr.Dropdown(choices=df['smoking_history'].unique().tolist(),
+                                     value=['never', 'current', 'former'],
+                                     multiselect=True, label="Riwayat Merokok")
+            in_gender = gr.Dropdown(choices=df['gender'].unique().tolist(),
+                                    value=df['gender'].unique().tolist(),
+                                    multiselect=True, label="Gender")
+        with gr.Column(scale=2):
+            with gr.Row():
+                in_age_start = gr.Slider(0, 100, value=20, step=1, label="Umur (Min)")
+                in_age_end = gr.Slider(0, 100, value=80, step=1, label="Umur (Max)")
+        with gr.Column(scale=1):
+            btn = gr.Button("🔄 Analisis Data", variant="primary")
+
+    with gr.Row():
+        out_summary = gr.Markdown()
+
+    with gr.Row():
+        out_scatter = gr.Plot()
+
+    with gr.Row():
+        out_pie = gr.Plot()
+        out_hist = gr.Plot()
+
+    btn.click(update_dashboard, inputs=[in_age_start, in_age_end, in_smoking, in_gender], outputs=[out_scatter, out_pie, out_hist, out_summary])
+    app.load(update_dashboard, inputs=[in_age_start, in_age_end, in_smoking, in_gender], outputs=[out_scatter, out_pie, out_hist, out_summary])
+
+app.launch()

requirements.txt

@@ -0,0 +1,3 @@
+pandas
+plotly
+gradio