我有数据
[{"state": "Florida",
"shortname": "FL",
"info": {"governor": "Rick Scott"},
"counties": [{"name": "Dade",
"population": 12345,
"Attributes": [
{
"capture_date": "2020-01-29",
"Spirit_code": "TRLQR",
"value": 1
},
{
"capture_date": "2020-01-29",
"Spirit_code": "HAVPN",
"value": 57000
}
]},
{"name": "Broward",
"population": 40000,
"Attributes": [
{
"capture_date": "2020-01-29",
"Spirit_code": "GMSTP",
"value": 14
},
{
"capture_date": "2020-01-29",
"Spirit_code": "GWTPN",
"value": 11212
}
]
},
{"name": "Palm Beach",
"population": 60000,
"Attributes": [{
"capture_date": "2020-01-29",
"Spirit_code": "YGHMN",
"value": 154.01
},
{
"capture_date": "2020-01-29",
"Spirit_code": "CXZASD",
"value": 154.01
}]
}
]},
{"state": "Ohio",
"shortname": "OH",
"info": {"governor": "John Kasich"},
"counties": [{"name": "Summit", "population": 1234,
"Attributes": [{
"capture_date": "2020-01-29",
"Spirit_code": "QWERTY",
"value": 154.01
},
{
"capture_date": "2020-01-29",
"Spirit_code": "JKLGH",
"value": 154.01
}]
},
{"name": "Cuyahoga", "population": 1337,
"Attributes": [{
"capture_date": "2020-01-29",
"Spirit_code": "ASDF",
"value": 154.01
},
{
"capture_date": "2020-01-29",
"Spirit_code": "POIUY",
"value": 154.01
}]
}],
}
]
我正在寻找结果：
state, shortname, name, population, attirbute.capture_date, attirbute.spirit_code, attirbute.value
florida, FL ,Dade, 12345 , 2020-0-29 , TRLQR , 1
florida, FL ,Dade, 12345 , 2020-0-29 , HAVPN , 57000
florida, FL ,Broward, 40000 , 2020-0-29 , GMSTP , 14
florida, FL ,Broward, 40000 , 2020-0-29 , GWTPN , 11212
florida, FL ,Palm Beach, 60000 , 2020-0-29 , YGHMN , 154.01
florida, FL ,Palm Beach, 60000 , 2020-0-29 , YGHMN , 154.01
florida, FL ,Palm Beach, 60000 , 2020-0-29 , CXZASD , 154.01
基本上标准化嵌套json中的键属性。关键字：“属性”。
json_normalize(data["data"], ["counties", "Attributes"], ["state", "shortname", ["counties", "name"], ["counties", "population"]])
我收到错误：
TypeError: {'name': 'Dade', 'population': 12345, 'Attributes': [{'capture_date': '2020-01-29', 'Spirit_code': 'TRLQR', 'value': 1}, {'capture_date': '2020-01-29', 'Spirit_code': 'HAVPN', 'value': 57000}]} has non iterable value 12345 for path ['population']. Must be iterable or null.
但是如果我跑步：
plots_in = json_normalize(data["data"], ["counties", "Attributes"],
["state", "shortname", ["counties", "name"]])
我得到结果：
capture_date Spirit_code value state shortname counties.name
0 2020-01-29 TRLQR 1.00 Florida FL Dade
1 2020-01-29 HAVPN 57000.00 Florida FL Dade
2 2020-01-29 GMSTP 14.00 Florida FL Broward
3 2020-01-29 GWTPN 11212.00 Florida FL Broward
4 2020-01-29 YGHMN 154.01 Florida FL Palm Beach
5 2020-01-29 CXZASD 154.01 Florida FL Palm Beach
6 2020-01-29 QWERTY 154.01 Ohio OH Summit
7 2020-01-29 JKLGH 154.01 Ohio OH Summit
8 2020-01-29 ASDF 154.01 Ohio OH Cuyahoga
9 2020-01-29 POIUY 154.01 Ohio OH Cuyahoga
与填充密钥中的整数有关吗？因为如果我运行以下命令，仍然会出现相同的错误：
plots_in = json_normalize(data["data"], ["counties", "population"])
[请说明，如果有人知道下面发生了什么？
检查您的熊猫版本。如果它是熊猫1.0.0，则很可能与以下内容有关：json_normalize in 1.0.0 with meta path specified - expects iterable #31507
我遇到了与在Linux中重新安装我的开发环境完全相同的问题，包括使用pandas 1.0.0安装所有最新软件包。经过一番搜索后，我找到了上面的链接，然后通过首先卸载来删除pandas 1.0.0并安装了pandas 0.25.3：
pip3 uninstall pandas # or pip uninstall pandas
然后：
pip3 install pandas==0.25.3 # or pip install pandas==0.25.3
此后，一切正常，就像安装最新的熊猫之前一样。
这是一种方法：
# s is the given json sample
df = pd.io.json.json_normalize(s)
# unnest the list
df['counties'] = df['counties'].str[0]
# convert counties dict into cols
df = pd.concat([df, df.pop('counties').apply(pd.Series)], axis=1)
# unnest the list
df['Attributes'] = df['Attributes'].str[0]
# convert Attributes dict into cols
df = pd.concat([df, df.pop('Attributes').apply(pd.Series)], axis=1)
print(df)
state shortname info.governor name population capture_date \
0 Florida FL Rick Scott Dade 12345 2020-01-29
1 Ohio OH John Kasich Summit 1234 2020-01-29
Spirit_code value
0 TRLQR 1.00
1 QWERTY 154.01