熊猫价值查找但有重复值

Question

我有一个清单，列有物品的价格，这些元素的顺序，也很重要。我也有一个数据与这些清单中的项目和它们的相关价格。我试图遍历每个列表，并将列表中的price元素替换为相应的条目。我的问题是，有两种产品的价格是一样的。目前，我的代码只是将这两个重复的定价项目添加到列表中，但我希望它为这两个项目创建一个单独的列表。

当前代码：

data = {'Item':['Apples', 'Cereal', 'Corn', 'Pasta', 'Detergent', 'Coffee', 'Ketchup', 'Oats', 'Olive Oil'],
        'Price':[4, 2, 6, 5, 10, 9, 2, 3, 1]}
 
df = pd.DataFrame(data)

combos = [[4, 2, 3, 6], [2, 10, 2, 4], [6, 1, 10, 2]]

testing = []

for list in combos:
    output = df.set_index('Price').loc[list, 'Item'].to_numpy().tolist()
    testing.append(output)
print(testing)

输出：

[['Apples', 'Cereal', 'Ketchup', 'Oats', 'Corn'], ['Cereal', 'Ketchup', 'Detergent', 'Cereal', 'Ketchup', 'Apples'], ['Corn', 'Olive Oil', 'Detergent', Cereal, 'Ketchup']]

我想要的结果：

[['Apples', 'Cereal', 'Oats', 'Corn'], ['Cereal', 'Detergent', 'Cereal', 'Apples'], ['Cereal', 'Detergent', 'Ketchup', 'Apples'], ['Ketchup', 'Detergent', 'Cereal', 'Apples'], ['Ketchup', 'Detergent', 'Ketchup', 'Apples'], ['Corn', 'Olive Oil', 'Detergent', 'Cereal'], ['Corn', 'Olive Oil', 'Detergent', 'Ketchup']]

Answer 1

使用itertools.product和chain的一种方法

from itertools import product, chain

prices = df.groupby("Price")["Item"].apply(list)
list(chain.from_iterable(product(*prices.loc[c]) for c in combos))

输出：

[('Apples', 'Cereal', 'Oats', 'Corn'),
 ('Apples', 'Ketchup', 'Oats', 'Corn'),
 ('Cereal', 'Detergent', 'Cereal', 'Apples'),
 ('Cereal', 'Detergent', 'Ketchup', 'Apples'),
 ('Ketchup', 'Detergent', 'Cereal', 'Apples'),
 ('Ketchup', 'Detergent', 'Ketchup', 'Apples'),
 ('Corn', 'Olive Oil', 'Detergent', 'Cereal'),
 ('Corn', 'Olive Oil', 'Detergent', 'Ketchup')]

Answer 2

您还可以使用pd.MultiIndex.from_product来生产笛卡尔产品：

prices = df.groupby("Price")["Item"].apply(list)
out = []
for combo in combos:
    product = pd.MultiIndex.from_product(prices.loc[combo]).tolist() 
    out.extend(map(list, product))

输出：

[['Apples', 'Cereal', 'Oats', 'Corn'], 
 ['Apples', 'Ketchup', 'Oats', 'Corn'], 
 ['Cereal', 'Detergent', 'Cereal', 'Apples'], 
 ['Cereal', 'Detergent', 'Ketchup', 'Apples'], 
 ['Ketchup', 'Detergent', 'Cereal', 'Apples'], 
 ['Ketchup', 'Detergent', 'Ketchup', 'Apples'], 
 ['Corn', 'Olive Oil', 'Detergent', 'Cereal'], 
 ['Corn', 'Olive Oil', 'Detergent', 'Ketchup']]