Python dict分组并求和多个值 [英] Python dict group and sum multiple values

问题描述

我在dict格式列表中有一组数据，如下所示:

I have a set of data in the list of dict format like below:

data = [
    {'name': 'A', 'tea':5, 'coffee':6},
    {'name': 'A', 'tea':2, 'coffee':3},
    {'name': 'B', 'tea':7, 'coffee':1},
    {'name': 'B', 'tea':9, 'coffee':4},
]

我正在尝试按名称"分组并分别对茶"和咖啡"进行求和

I'm trying to group by 'name' and sum the 'tea' separately and 'coffee' separately

最终分组的数据必须采用以下格式:

The final grouped data must be in the this format:

grouped_data = [
    {'name': 'A', 'tea':7, 'coffee':9},
    {'name': 'B', 'tea':16, 'coffee':5},
]

我尝试了一些步骤:

from collections import Counter
c = Counter()
for v in data:
    c[v['name']] += v['tea']

my_data = [{'name': name, 'tea':tea} for name, tea in c.items()]
for e in my_data:
    print e

以上步骤返回了以下输出:

The above step returned the following output:

{'name': 'A', 'tea':7,}
{'name': 'B', 'tea':16}

只有我可以对密钥'tea'求和，我无法对密钥'coffee'求和，请您帮忙解决此问题，以获取grouped_data格式

Only I can sum the key 'tea', I'm not able to get the sum for the key 'coffee', can you guys please help to solve this solution to get the grouped_data format

推荐答案

使用pandas:

df = pd.DataFrame(data)
df

   coffee name  tea
0       6    A    5
1       3    A    2
2       1    B    7
3       4    B    9


g = df.groupby('name', as_index=False).sum()
g

  name  coffee  tea
0    A       9    7
1    B       5   16

最后一步，df.to_dict:

d = g.to_dict('r')

d
[{'coffee': 9, 'name': 'A', 'tea': 7}, {'coffee': 5, 'name': 'B', 'tea': 16}]

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