这个产品适合装在纸箱里吗?

import itertools

values = carton.values[:, 1:]

combi = [np.column_stack([x,y,z]) 
        for x, y, z in itertools.permutations([values[:,0],values[:,1],values[:,2]])]
new_values = np.concatenate(combi)
new_index = carton.carton_id.tolist() * len(combi)
new = np.column_stack([new_index, new_values])
new_carton = pd.DataFrame(new, columns=['carton_id', 'length', 'width', 'height'])


df = pd.merge(product, new_carton, how='cross', suffixes=('_prod', '_cart'))
df = df[(df.length_cart>df.length_prod) 
   & (df.width_cart>df.width_prod)
   & (df.height_cart>df.height_prod)]
df = df[['product_id', 'carton_id']].drop_duplicates()

print(df)

   product_id  carton_id
0         100         66
1         100         67

这里有一种方法:

# take the `id` columns to indexes
p = p.set_index("product_id")
c = c.set_index("carton_id")

# get products row-wise
pp = p.prod(axis=1).to_numpy()
cc = c.prod(axis=1).to_numpy()

# compare each row of `pp` against each row of `cc`
cross_compare = np.less.outer(pp, cc)

# matmul via making use of booleans are integers
# to select the appropriate carton_id's
result = cross_compare.dot(c.index + " ")

# put the result into a dataframe
out = pd.DataFrame({"product_id": p.index, "carton_id": result})

得到

>>> out

   product_id  carton_id
0         100  66 67 68
1         101  66 67 68