df['month'] = df['date'].dt.month
df['day_of_week'] = df['date'].dt.dayofweek
# Lag feature
df['top_number_lag1'] = df.groupby('badu_id')['top_number'].shift(1)
If you have a tabular dataset with columns like location, name_badu, top_number, here’s how to prepare deep features:
Never pay the first price. If they ask LKR 25,000 for a Number 1 Top bale, counter with LKR 18,000. Typically, the deal closes at LKR 20,000-22,000. negombo badu number top
# Mean top_number per Negombo area
df['negombo_mean_top'] = df.groupby('negombo_zone')['top_number'].transform('mean')
# Interaction between Negombo region and Badu subtype
df['negombo_badu_interact'] = df['negombo_zone_code'] * df['badu_code']
Why is the Negombo Badu Number Top so popular? The math is simple. df['month'] = df['date']
Cost of a Number 1 Top Bale (50 pieces): LKR 20,000
Cost per Top: LKR 400 If you have a tabular dataset with columns
Selling Strategy:
Total Revenue: LKR 40,000
Net Profit: LKR 20,000 (100% ROI on a single bale)
Vendors who specialize in Negombo Badu Number Top often sell out within a weekend at local Senas (fairs) or Polas (weekly markets).