Ani*_*ari 1 python json dictionary pandas data-science
假设我有一个 API 响应:
{
    "fact": {
        "UP": [{
            "SCODE": "CNB",
            "SNAME": "Kanpur Central"
        }, {
            "SCODE": "JHS",
            "SNAME": "Jhansi Junction"
        }],
        "MP": [{
            "SCODE": "BPL",
            "SNAME": "Bhopal Junction"
        }, {
            "SCODE": "JBP",
            "SNAME": "Jabalpur Junction"
        }]
    }
}
我必须将其转换为如下所示的数据帧(预期输出):
fact    SCODE   SNAME
UP      CNB     Kanpur Central
UP      JHS     Jhansi Junction
MP      BPL     Bhopal Junction
MP      JBP     Jabalpur Junction
我的努力:我尝试使用 json_normalize() 但没有达到预期的输出:
{
    "fact": {
        "UP": [{
            "SCODE": "CNB",
            "SNAME": "Kanpur Central"
        }, {
            "SCODE": "JHS",
            "SNAME": "Jhansi Junction"
        }],
        "MP": [{
            "SCODE": "BPL",
            "SNAME": "Bhopal Junction"
        }, {
            "SCODE": "JBP",
            "SNAME": "Jabalpur Junction"
        }]
    }
}
一种选择是用 python 重塑:
df = pd.DataFrame([{'fact': k, **item}
                   for k, lst in response['fact'].items()
                   for item in lst])
  fact SCODE              SNAME
0   UP   CNB     Kanpur Central
1   UP   JHS    Jhansi Junction
2   MP   BPL    Bhopal Junction
3   MP   JBP  Jabalpur Junction
pandas通过explode+的选项:apply pd.Series
df = (
    pd.DataFrame(response)['fact']
        .explode()
        .apply(pd.Series)
        .rename_axis('fact')
        .reset_index()
)
  fact SCODE              SNAME
0   MP   BPL    Bhopal Junction
1   MP   JBP  Jabalpur Junction
2   UP   CNB     Kanpur Central
3   UP   JHS    Jhansi Junction
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