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"
}]
}
}
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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
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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"
}]
}
}
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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])
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fact SCODE SNAME
0 UP CNB Kanpur Central
1 UP JHS Jhansi Junction
2 MP BPL Bhopal Junction
3 MP JBP Jabalpur Junction
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pandas通过explode+的选项:apply pd.Series
df = (
pd.DataFrame(response)['fact']
.explode()
.apply(pd.Series)
.rename_axis('fact')
.reset_index()
)
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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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