Python如何添加多个列表的和

Question

下面是列表的列表。如何将“完全黑色”和“全色”的总和添加到一个保持“帐户ID”和“帐户名称”不变的列表中？

[[{'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'}]]

因此，结果将是：

[{'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

让我们用熊猫。

#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}]

详细信息：

首先，我们使用列表理解和熊猫dataframe构造函数为原始列表中的每个元素和字典构建数据。

接下来，使用pd.concat将这两者(在本例中为dataframes合并为一个组合的dataframe )。

使用“组”和“和”来聚合“总颜色”和“总黑色”的值。

最后，重置索引和to_dict输出组合数据作为一个字典。

Answer 2

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'}]
]

非常类似于ScottBoston

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 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，对每个包含的列表重复这一步骤。