Create app.py

app.py

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+import pandas as pd
+import matplotlib
+matplotlib.use("Agg")
+import matplotlib.pyplot as plt
+import gradio as gr
+import os
+import tempfile
+
+def plot_top_100_mak(excel_file):
+    # Baca file Excel dari path
+    df = pd.read_excel(excel_file)
+
+    # Tangani nilai kosong
+    df["MAK"] = df["MAK"].fillna("Unknown")
+    df["Nominal"] = pd.to_numeric(df["Nominal"], errors="coerce").fillna(0)
+
+    # Ambil 100 MAK dengan nominal terbesar
+    top_100 = (
+        df.groupby("MAK", as_index=False)["Nominal"]
+        .sum()
+        .sort_values("Nominal", ascending=False)
+        .head(100)
+    )
+
+    # Konversi ke juta
+    top_100["Nominal"] = top_100["Nominal"] / 1_000_000
+
+    # Plot
+    plt.figure(figsize=(16, 9))
+    bars = plt.bar(top_100["MAK"], top_100["Nominal"])
+    plt.xlabel("MAK")
+    plt.ylabel("Nominal (Juta)")
+    plt.title("Top 100 MAK dengan Nominal Terbesar")
+    plt.xticks(rotation=90)
+    plt.tight_layout()
+
+    # Label nilai
+    for bar in bars:
+        height = bar.get_height()
+        plt.text(
+            bar.get_x() + bar.get_width() / 2,
+            height,
+            f"{height:,.2f}",
+            ha="center",
+            va="bottom",
+            fontsize=7,
+        )
+
+    # Simpan ke file sementara
+    tmp_dir = tempfile.mkdtemp()
+    output_path = os.path.join(tmp_dir, "top_100_mak.png")
+    plt.savefig(output_path, dpi=150)
+    plt.close()
+
+    return "Bar chart berhasil dibuat.", output_path
+
+
+with gr.Blocks() as demo:
+    gr.Markdown(
+        """
+        ## 📊 Top 100 MAK dengan Nominal Terbesar
+        Unggah file Excel yang memiliki kolom **MAK** dan **Nominal**
+        """
+    )
+
+    file_input = gr.File(
+        label="Unggah File Excel",
+        file_types=[".xlsx", ".xls"],
+    )
+
+    result_text = gr.Textbox(label="Status")
+    result_image = gr.Image(label="Bar Chart")
+
+    submit_btn = gr.Button("Proses")
+
+    submit_btn.click(
+        fn=plot_top_100_mak,
+        inputs=file_input,
+        outputs=[result_text, result_image],
+    )
+
+demo.launch()