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import pandas as pd
import gradio as gr
def process_data(file):
try:
# file adalah path di Hugging Face Spaces
df = pd.read_excel(file)
output_data = []
no = 1
char1 = char2 = char3 = char4 = ""
previous_char3 = ""
nominal = tipe = 0
anggaran1 = anggaran2 = anggaran3 = 0
total_nominal = 0
column_names = df.columns.tolist()
for _, row in df.iterrows():
kode = str(row[column_names[0]]).strip()
anggaran = row[column_names[3]]
if kode and kode[0] in ["3", "6"]:
char1 = kode
anggaran3 = anggaran
elif kode.startswith("0"):
char2 = kode
elif kode != "nan" and kode.isalpha():
char3 = kode
previous_char3 = char3
anggaran1 = anggaran
elif kode.startswith("5"):
char4 = kode
anggaran2 = anggaran
if pd.isna(row[column_names[9]]):
nominal = row[column_names[10]]
tipe = row[column_names[13]]
else:
nominal = row[column_names[9]]
tipe = row[column_names[11]]
if char3 == "":
char3 = previous_char3
mak = f"{char1}.{char2}.{char3}.{char4}"
output_data.append({
"No": no,
"MAK": mak,
"Anggaran3": anggaran3,
"Anggaran1": anggaran1,
"Anggaran2": anggaran2,
"Nominal": nominal,
"Tipe": tipe
})
no += 1
char3 = ""
if pd.notna(nominal):
total_nominal += float(nominal)
output_data.append({
"No": "",
"MAK": "",
"Anggaran3": "",
"Anggaran1": "",
"Anggaran2": "",
"Nominal": f"Total Nominal: {total_nominal:.0f}",
"Tipe": ""
})
output_df = pd.DataFrame(output_data)
output_file = "/tmp/processed_data.xlsx"
output_df.to_excel(output_file, index=False)
return output_file
except Exception as e:
return f"Error: {e}"
with gr.Blocks(title="Konvert Mata Anggaran Sakti") as demo:
gr.Markdown("### Konvert Mata Anggaran Sakti")
gr.Markdown("Unggah file Excel, sistem akan mengonversi dan menghasilkan file Excel baru.")
input_file = gr.File(label="Upload Excel File", file_types=[".xlsx"])
output_file = gr.File(label="Download Hasil")
btn = gr.Button("Proses")
btn.click(process_data, inputs=input_file, outputs=output_file)
demo.launch()
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