如何在另一列的条件下从一列中获取值的总和

Question

对于下图中显示的示例数据：

如何获得一列中出现的相似项目的数量，条件是 customer_id 相同？

ls=[]
for i in data['customer_id']:
    sum=0
    for j in data['category']:    
        if i == j[0]:
            sum+=j[1]
    ls.append(sum)

简而言之：

[food and fruit, vegetable, bakery and bread, cookies snacks or candies, seafoods and meat] 
customer_id[0] = [4,9,5,1,0]

Answer 1

假设您的数据被加载到 pandas dataframe 中，您可以使用：

# Sample data
labels = ["a", "b", "c", "a, b, c", "b, c"]
df = pd.DataFrame({
    "customer_id": [0, 1]*10,
    "category": [labels[np.random.randint(0,len(labels ))] for i in range(20)]
})

# Count per group and pivot the rows to columns
df.groupby(['customer_id', 'category']).size().reset_index().pivot_table(
    0, ['customer_id'], 'category').fillna(0).rename_axis(
        None, axis=1).reset_index()

output：

    customer_id   a      a, b, c      b      b, c      c
0   0           2.0          1.0    1.0       5.0    1.0
1   1           2.0          0.0    4.0       1.0    3.0