Python如何添加多个列表的总和

Question

以下是列表列表。如何将“Total Black”和“Total Color”的总和添加到一个列表中，同时保持“Account ID”和“Account Name”相同？

[[{'Total Black': 3, 'Total Color': 2, 'Account ID': '2222', 'Account Name': 'Moe'}, 
  {'Total Black': 5, 'Total Color': 4, 'Account ID': '3333', 'Account Name': 'Larry'}, 
  {'Total Black': 9, 'Total Color': 6, 'Account ID': '4444', 'Account Name': 'Curly'}], 
 [{'Total Black': 8, 'Total Color': 4, 'Account ID': '2222', 'Account Name': 'Moe'}, 
  {'Total Black': 2, 'Total Color': 7, 'Account ID': '3333', 'Account Name': 'Larry'}, 
  {'Total Black': 11, 'Total Color': 9, 'Account ID': '4444', 'Account Name': 'Curly'}]]

所以结果是：

[{'Total Black': 11, 'Total Color': 6, 'Account ID': '2222', 'Account Name': 
'Moe'}, {'Total Black': 7, 'Total Color': 11, 'Account ID': '3333', 'Account 
Name': 'Larry'}, {'Total Black': 20, 'Total Color': 15, 'Account ID': 4444, 
'Account Name': 'Curly'}]

Answer 1

设置

thing = [
    [{'Total Black': 3, 'Total Color': 2, 'Account ID': '2222', 'Account Name': 'Moe'}, 
     {'Total Black': 5, 'Total Color': 4, 'Account ID': '3333', 'Account Name': 'Larry'}, 
     {'Total Black': 9, 'Total Color': 6, 'Account ID': '4444', 'Account Name': 'Curly'}], 
    [{'Total Black': 8, 'Total Color': 4, 'Account ID': '2222', 'Account Name': 'Moe'}, 
     {'Total Black': 2, 'Total Color': 7, 'Account ID': '3333', 'Account Name': 'Larry'}, 
     {'Total Black': 11, 'Total Color': 9, 'Account ID': '4444', 'Account Name': 'Curly'}]
]

---

与 ScottBoston 非常相似

pd.DataFrame(sum(thing, [])).groupby(
    ['Account ID', 'Account Name'], as_index=False
).sum().to_dict('r')

---

merge_with

from itertools import chain
from toolz.dicttoolz import merge_with
from collections import defaultdict

idkey = ('Account ID', 'Account Name')

x = defaultdict(list)
for d in map(dict, chain(*thing)):
  x[(*map(d.pop, idkey),)].append(d)

[{**dict(zip(idkey, key)), **merge_with(sum, *d)} for key, d in x.items()]

[{'Account ID': '2222',
  'Account Name': 'Moe',
  'Total Black': 11,
  'Total Color': 6},
 {'Account ID': '3333',
  'Account Name': 'Larry',
  'Total Black': 7,
  'Total Color': 11},
 {'Account ID': '4444',
  'Account Name': 'Curly',
  'Total Black': 20,
  'Total Color': 15}]

Answer 2

让我们使用熊猫。

#From @C14L setup:

li = [
    [
        {'Total Black': 3, 'Total Color': 2, 'Account ID': '2222', 'Account Name': 'Moe'},
        {'Total Black': 5, 'Total Color': 4, 'Account ID': '3333', 'Account Name': 'Larry'},
        {'Total Black': 9, 'Total Color': 6, 'Account ID': '4444', 'Account Name': 'Curly'}
    ],
    [
        {'Total Black': 8, 'Total Color': 4, 'Account ID': '2222', 'Account Name': 'Moe'},
        {'Total Black': 2, 'Total Color': 7, 'Account ID': '3333', 'Account Name': 'Larry'},
        {'Total Black': 11, 'Total Color': 9, 'Account ID': '4444', 'Account Name': 'Curly'}
    ]
]

pd.concat([pd.DataFrame(li[i]) for i in range(len(li))])\
  .groupby(['Account ID','Account Name'])\
  .sum()\
  .reset_index()\
  .to_dict(orient='records')

输出：

[{'Account ID': '2222',
  'Account Name': 'Moe',
  'Total Black': 11,
  'Total Color': 6},
 {'Account ID': '3333',
  'Account Name': 'Larry',
  'Total Black': 7,
  'Total Color': 11},
 {'Account ID': '4444',
  'Account Name': 'Curly',
  'Total Black': 20,
  'Total Color': 15}]

详情：

首先，我们使用列表推导和 pandas 数据框构造函数为原始列表列表中的每个元素构建数据框和字典。

接下来，使用 pd.concat 将这两个数据帧（在本例中为数据帧）放在一个组合数据帧中。

使用 groupby 和 sum 来聚合 Total Color 和 Total Black 的值。

最后，重置 index 和 to_dict 以将组合数据帧输出为字典。

Answer 3

li = [
    [
        {'Total Black': 3, 'Total Color': 2, 'Account ID': '2222', 'Account Name': 'Moe'},
        {'Total Black': 5, 'Total Color': 4, 'Account ID': '3333', 'Account Name': 'Larry'},
        {'Total Black': 9, 'Total Color': 6, 'Account ID': '4444', 'Account Name': 'Curly'}
    ],
    [
        {'Total Black': 8, 'Total Color': 4, 'Account ID': '2222', 'Account Name': 'Moe'},
        {'Total Black': 2, 'Total Color': 7, 'Account ID': '3333', 'Account Name': 'Larry'},
        {'Total Black': 11, 'Total Color': 9, 'Account ID': '4444', 'Account Name': 'Curly'}
    ]
]

result = [
    {
        'sum': x['Total Black'] + x['Total Color'],
        'Account ID': x['Account ID'],
        'Account Name': x['Account Name']
    } for x in li[0]
]

给出第一个子列表的结果

[
    {'sum': 5, 'Account ID': '2222', 'Account Name': 'Moe'},
    {'sum': 9, 'Account ID': '3333', 'Account Name': 'Larry'},
    {'sum': 15, 'Account ID': '4444', 'Account Name': 'Curly'},
]

这就是你要找的吗？

现在您只需要遍历外部列表以对每个包含的列表重复此操作。

Answer 4

没有 Pandas 解决方案：

from itertools import groupby
from operator import itemgetter

orders_list = [[{'Total Black': 3, 'Total Color': 2, 'Account ID': '2222', 'Account Name': 'Moe'}, 
  {'Total Black': 5, 'Total Color': 4, 'Account ID': '3333', 'Account Name': 'Larry'}, 
  {'Total Black': 9, 'Total Color': 6, 'Account ID': '4444', 'Account Name': 'Curly'}], 
 [{'Total Black': 8, 'Total Color': 4, 'Account ID': '2222', 'Account Name': 'Moe'}, 
  {'Total Black': 2, 'Total Color': 7, 'Account ID': '3333', 'Account Name': 'Larry'}, 
  {'Total Black': 11, 'Total Color': 9, 'Account ID': '4444', 'Account Name': 'Curly'}]]


result_list = []

flattened_list = [item for sublist in orders_list for item in sublist]
grouper = itemgetter("Account ID", "Account Name")

for key, grp in groupby(sorted(flattened_list, key = grouper), grouper):
    temp_dict = dict(zip(["Account ID", "Account Name"], key))
    total_black_count = 0
    total_colors_count = 0
    for element in grp:
          total_black_count += element['Total Black']
          total_colors_count += element['Total Color']

    temp_dict["Total Color"] = total_colors_count
    temp_dict["Total Black"] = total_black_count
    result_list.append(temp_dict)

for dictionary in result_list:
    for key, values in dictionary.items():
        print(f"{key}: {values}")

DEMO FIDDLE