Python 如何将这种列形式的嵌套JSON转换为数据帧
我可以将这种列格式的嵌套JSON格式读入pandas JSON格式 Python脚本 更新 我想将下面的JSON方案转换为表格格式,如表所示,如何 JSON方案 Pandas有一个功能(从0.13开始),直接来自文档:Python 如何将这种列形式的嵌套JSON转换为数据帧,python,pandas,Python,Pandas,我可以将这种列格式的嵌套JSON格式读入pandas JSON格式 Python脚本 更新 我想将下面的JSON方案转换为表格格式,如表所示,如何 JSON方案 Pandas有一个功能(从0.13开始),直接来自文档: In [205]: from pandas.io.json import json_normalize In [206]: data = [{'state': 'Florida', .....: 'shortname': 'FL', ...
In [205]: from pandas.io.json import json_normalize
In [206]: data = [{'state': 'Florida',
.....: 'shortname': 'FL',
.....: 'info': {
.....: 'governor': 'Rick Scott'
.....: },
.....: 'counties': [{'name': 'Dade', 'population': 12345},
.....: {'name': 'Broward', 'population': 40000},
.....: {'name': 'Palm Beach', 'population': 60000}]},
.....: {'state': 'Ohio',
.....: 'shortname': 'OH',
.....: 'info': {
.....: 'governor': 'John Kasich'
.....: },
.....: 'counties': [{'name': 'Summit', 'population': 1234},
.....: {'name': 'Cuyahoga', 'population': 1337}]}]
.....:
In [207]: json_normalize(data, 'counties', ['state', 'shortname', ['info', 'governor']])
Out[207]:
name population info.governor state shortname
0 Dade 12345 Rick Scott Florida FL
1 Broward 40000 Rick Scott Florida FL
2 Palm Beach 60000 Rick Scott Florida FL
3 Summit 1234 John Kasich Ohio OH
4 Cuyahoga 1337 John Kasich Ohio OH
也许这就是你要找的?我总是忘记它的存在,所以我重新实现了几次-(@DSM我也是…公平地说,这是“最近的”。:)@Yhayden谢谢你的回答,你能给我一些新问题的提示吗@Andy Hayden如果
'countries'
是'info'
的孩子呢?元是什么?我仍然在测试如何解析'info':['countries']
值。
"data":[
{
"year":"2009",
"values":[
{
"Actual":"(0.2)"
},
{
"Upper End of Range":"-"
},
{
"Upper End of Central Tendency":"-"
},
{
"Lower End of Central Tendency":"-"
},
{
"Lower End of Range":"-"
}
]
},
{
"year":"2010",
"values":[
{
"Actual":"2.8"
},
{
"Upper End of Range":"-"
},
{
"Upper End of Central Tendency":"-"
},
{
"Lower End of Central Tendency":"-"
},
{
"Lower End of Range":"-"
}
]
},...
]
In [205]: from pandas.io.json import json_normalize
In [206]: data = [{'state': 'Florida',
.....: 'shortname': 'FL',
.....: 'info': {
.....: 'governor': 'Rick Scott'
.....: },
.....: 'counties': [{'name': 'Dade', 'population': 12345},
.....: {'name': 'Broward', 'population': 40000},
.....: {'name': 'Palm Beach', 'population': 60000}]},
.....: {'state': 'Ohio',
.....: 'shortname': 'OH',
.....: 'info': {
.....: 'governor': 'John Kasich'
.....: },
.....: 'counties': [{'name': 'Summit', 'population': 1234},
.....: {'name': 'Cuyahoga', 'population': 1337}]}]
.....:
In [207]: json_normalize(data, 'counties', ['state', 'shortname', ['info', 'governor']])
Out[207]:
name population info.governor state shortname
0 Dade 12345 Rick Scott Florida FL
1 Broward 40000 Rick Scott Florida FL
2 Palm Beach 60000 Rick Scott Florida FL
3 Summit 1234 John Kasich Ohio OH
4 Cuyahoga 1337 John Kasich Ohio OH