我正在研究2015年至2020年世界幸福报告的交互式可视化。数据分为6个csv文件。使用熊猫，我成功清理了数据并将它们连接到一个具有以下格式的大JSON文件中：
[
{
"Country": "Switzerland",
"Year": 2015,
"Happiness Rank": 1,
"Happiness Score": 7.587000000000001,
},
{
"Country": "Iceland",
"Year": 2015,
"Happiness Rank": 2,
"Happiness Score": 7.561,
},
{
"Country": "Switzerland",
"Year": 2016,
"Happiness Rank": 2,
"Happiness Score": 7.5089999999999995,
},
{
"Country": "Iceland",
"Year": 2016,
"Happiness Rank": 3,
"Happiness Score": 7.501,
},
{
"Country": "Switzerland",
"Year": 2017,
"Happiness Rank": 3,
"Happiness Score": 7.49399995803833,
},
{
"Country": "Iceland",
"Year": 2017,
"Happiness Rank": 1,
"Happiness Score": 7.801,
}
]
现在，我想以编程方式格式化JSON文件，使其具有以下格式：
{
"2015": {
"Switzerland": {
"Happiness Rank": 1,
"Happiness Score": 7.587000000000001
},
"Iceland": {
"Happiness Rank": 2,
"Happiness Score": 7.561
}
},
"2016": {
"Switzerland": {
"Happiness Rank": 2,
"Happiness Score": 7.5089999999999995
},
"Iceland": {
"Happiness Rank": 3,
"Happiness Score": 7.501
}
},
"2017": {
"Switzerland": {
"Happiness Rank": 3,
"Happiness Score": 7.49399995803833
},
"Iceland": {
"Happiness Rank": 1,
"Happiness Score": 7.801
}
}
}
由于有900多个不同的（国家/地区）对，因此必须以编程方式完成。我想要这种格式的JSON，因为它使JSON文件更具可读性，并且使选择合适的数据更加容易。如果我想要2015年冰岛的排名，那么我可以data[2015]["Iceland"]["Happiness Rank"]
有谁知道最简单/最方便的方式在Python中执行此操作？
如果data是您的原始字典清单：
def by_year(data):
from itertools import groupby
from operator import itemgetter
retain_keys = ("Happiness Rank", "Happiness Score")
for year, group in groupby(data, key=itemgetter("Year")):
as_tpl = tuple(group)
yield str(year), dict(zip(map(itemgetter("Country"), as_tpl), [{k: d[k] for k in retain_keys} for d in as_tpl]))
print(dict(by_year(data)))
输出：
{'2015': {'Switzerland': {'Happiness Rank': 1, 'Happiness Score': 7.587000000000001}, 'Iceland': {'Happiness Rank': 2, 'Happiness Score': 7.561}}, '2016': {'Switzerland': {'Happiness Rank': 2, 'Happiness Score': 7.5089999999999995}, 'Iceland': {'Happiness Rank': 3, 'Happiness Score': 7.501}}, '2017': {'Switzerland': {'Happiness Rank': 3, 'Happiness Score': 7.49399995803833}, 'Iceland': {'Happiness Rank': 1, 'Happiness Score': 7.801}}}
>>>
假设字典中的字典data已经按年分组。
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