preprocessing for time series survival model

ts_survival_preprocess.py

# Filtering the departments in config
sales = sales[sales.dept_id.isin(DEPTS)]
# sort data
sales = sales.sort_values(by=['item_id', 'dept_id', 'cat_id', 'store_id', 	
                              'state_id'])
# melting sales columns into one column
index_columns = ['id','item_id','dept_id','cat_id','store_id','state_id']
sales = pd.melt(sales, 
                  id_vars = index_columns, 
                  var_name = 'd', 
                  value_name = 'sales')
# dropping unnecessary columns
sales = sales.drop(['cat_id','state_id','id'], axis=1)
# rolling up store level data on item level
sales = sales.groupby(['dept_id','item_id','d']).agg({'sales':np.sum})\
.reset_index()
# converting column 'd'  to int type for sorting on date
sales['d'] = [val.replace('d_','') for val in sales.d]
sales['d'] = pd.to_numeric(sales.d)
sales = sales.sort_values(by=['dept_id','item_id','d'], ignore_index=True)