generate-csv-cogm.py

import pandas as pd
import numpy as np
from datetime import datetime, timedelta
import random
import string

# Fungsi untuk menghasilkan tanggal acak
# Fungsi untuk menghasilkan tanggal acak dalam format DD/MM/YYYY
def generate_random_datetime(start_date, end_date):
    delta = end_date - start_date
    random_days = random.randint(0, delta.days)
    return start_date + timedelta(days=random_days)

# Fungsi untuk menghasilkan kode acak (misal: Order ID, Material Code, dll.)
def generate_random_code(length=10):
    return ''.join(random.choices(string.digits, k=length))

# Fungsi untuk menghasilkan deskripsi material acak
def generate_material_description():
    materials = [
        "EKO MIE 3KG NEW",
        "MIE EKO DUO (EM2)",
        "INDOMIE SEDAP",
        "SARIWANGI RENDANG",
        "MILO CHOCOLATE",
        "KAKAO TANPA GULA"
    ]
    return random.choice(materials)

# Fungsi untuk menghasilkan unit acak
def generate_unit():
    units = ["BOX", "PCS"]
    return random.choice(units)

# Fungsi untuk menghasilkan nilai acak
def generate_random_number(min_val, max_val):
    return random.randint(min_val, max_val)

# Konfigurasi tanggal awal dan akhir
start_date = datetime(2025, 1, 1)
end_date = datetime(2025, 12, 31)

# Jumlah baris data
num_rows = 1

# Daftar kolom
columns = [
    "Months",
    "Order",
    "Material",
    "Material description",
    "Qty in base un. + sign (MEINS)",
    "Quantity in base unit (MEINS)",
    "Base Unit of Measure (=MEINS)",
    "Quantity in unit of entry (ERFME)",
    "Unit of Entry (=ERFME)",
    "Qty in UoE + sign (ERFME)",
    "Controlling Area",
    "Movement Type",
    "Goods movement indic",
    "Posting Date",
    "Material Document",
    "Mat.document item",
    "Storage Location",
    "Batch",
    "Code",
    "Category",
    "Sub Cat",
    "Market",
    "konversi PCS",
    "KONV 902",
    "Kg/Box",              
    "konversi in KG" 
]

# Inisialisasi DataFrame
data = {col: [] for col in columns}
# Dapatkan datetime acak
random_datetime = generate_random_datetime(start_date, end_date)

# Generate 80.000 baris data
for _ in range(num_rows):
    # Months
    months = random_datetime.strftime("%d/%m/%Y")
    
    # Order
    order = generate_random_code(9)
    
    # Material
    material = generate_random_code(7)
    
    # Material description
    material_desc = generate_material_description()
    
    # Qty in base un. + sign (MEINS)
    qty_base_sign = generate_random_number(-1000, 1000)
    
    # Quantity in base unit (MEINS)
    qty_base_unit = abs(qty_base_sign)
    
    # Base Unit of Measure (=MEINS)
    base_unit = generate_unit()
    
    # Quantity in unit of entry (ERFME)
    qty_entry = generate_random_number(1, 1000)
    
    # Unit of Entry (=ERFME)
    entry_unit = generate_unit()
    
    # Qty in UoE + sign (ERFME)
    qty_uoe_sign = -qty_entry if random.random() < 0.5 else qty_entry
    
    # Controlling Area
    controlling_area = "PACO"
    
    # Movement Type
    movement_type = generate_random_number(900, 910)
    
    # Goods movement indic
    goods_movement_indic = generate_random_number(1, 5)
    
    # Posting Date
    posting_date = random_datetime.strftime("%d/%m/%Y")
    
    # Material Document
    mat_doc = generate_random_code(10)
    
    # Mat.document item
    mat_doc_item = generate_random_number(1, 100)
    
    # Storage Location
    storage_loc = f"E{generate_random_number(1, 100):03}"
    
    # Batch
    batch = generate_random_code(10)
    
    # Code
    code = f"{storage_loc}{material}"
    
    # Category
    category = random.choice(["Noodle Eko CP", "Noodle Eko", "Snack"])
    
    # Sub Cat
    sub_cat = random.choice(["Eko CP", "Eko", "Indomie"])
    
    # Market
    market = random.choice(["Lokal", "Ekspor", "Distributor"])
    
    # konversi PCS
    konv_pcs = generate_random_number(1, 1000)
    
    # KONV 902
    konv_902 = generate_random_number(1, 1000)

     # Kg/Box
    kg_per_box = round(random.uniform(0.1, 25.0), 2)

    # konversi in KG (contoh: qty_base_unit * kg_per_box)
    konversi_kg = round(qty_base_unit * kg_per_box, 2)
    
    # Append to data
    data["Months"].append(months)
    data["Order"].append(order)
    data["Material"].append(material)
    data["Material description"].append(material_desc)
    data["Qty in base un. + sign (MEINS)"].append(qty_base_sign)
    data["Quantity in base unit (MEINS)"].append(qty_base_unit)
    data["Base Unit of Measure (=MEINS)"].append(base_unit)
    data["Quantity in unit of entry (ERFME)"].append(qty_entry)
    data["Unit of Entry (=ERFME)"].append(entry_unit)
    data["Qty in UoE + sign (ERFME)"].append(qty_uoe_sign)
    data["Controlling Area"].append(controlling_area)
    data["Movement Type"].append(movement_type)
    data["Goods movement indic"].append(goods_movement_indic)
    data["Posting Date"].append(posting_date)
    data["Material Document"].append(mat_doc)
    data["Mat.document item"].append(mat_doc_item)
    data["Storage Location"].append(storage_loc)
    data["Batch"].append(batch)
    data["Code"].append(code)
    data["Category"].append(category)
    data["Sub Cat"].append(sub_cat)
    data["Market"].append(market)
    data["konversi PCS"].append(konv_pcs)
    data["KONV 902"].append(konv_902)
    data["Kg/Box"].append(kg_per_box)
    data["konversi in KG"].append(konversi_kg)


# Buat DataFrame
df = pd.DataFrame(data)

# Simpan ke file CSV
df.to_csv("generate_data_cogm.csv", index=False)

# Simpan ke file Excel (opsional)
df.to_excel("generate_data_cogm.xlsx", index=False)

print(f"Selesai! Berhasil membuat {len(df)} baris data.")