【发布时间】：2021-08-26 20:44:31
【问题描述】：
我有作为嵌套 JSON 的输出。如何获取这个嵌套的 JSON 结构并将其更改为数据框？
我认为有两个主要级别“行情”和“承运人”。我有兴趣将“引号”作为数据框中的行。
{
"Quotes" : [ {
"QuoteId" : 1,
"MinPrice" : 1765,
"Direct" : false,
"OutboundLeg" : {
"CarrierIds" : [ 881 ],
"OriginId" : 56949,
"DestinationId" : 45348,
"DepartureDate" : "2021-08-31T00:00:00"
},
"QuoteDateTime" : "2021-06-09T09:15:00"
}, {
"QuoteId" : 2,
"MinPrice" : 1774,
"Direct" : false,
"OutboundLeg" : {
"CarrierIds" : [ 881 ],
"OriginId" : 56949,
"DestinationId" : 45348,
"DepartureDate" : "2021-07-06T00:00:00"
},
"QuoteDateTime" : "2021-06-08T11:49:00"
}, {
"QuoteId" : 3,
"MinPrice" : 1792,
"Direct" : false,
"OutboundLeg" : {
"CarrierIds" : [ 881 ],
"OriginId" : 56949,
"DestinationId" : 45348,
"DepartureDate" : "2021-10-12T00:00:00"
},
"QuoteDateTime" : "2021-06-07T01:22:00"
}, {
"QuoteId" : 4,
"MinPrice" : 1792,
"Direct" : false,
"OutboundLeg" : {
"CarrierIds" : [ 881 ],
"OriginId" : 56949,
"DestinationId" : 45348,
"DepartureDate" : "2022-03-01T00:00:00"
},
"QuoteDateTime" : "2021-06-07T03:28:00"
}, {
"QuoteId" : 5,
"MinPrice" : 2458,
"Direct" : false,
"OutboundLeg" : {
"CarrierIds" : [ 881 ],
"OriginId" : 56949,
"DestinationId" : 45348,
"DepartureDate" : "2021-06-19T00:00:00"
},
"QuoteDateTime" : "2021-06-07T19:28:00"
}, {
"QuoteId" : 6,
"MinPrice" : 2462,
"Direct" : false,
"OutboundLeg" : {
"CarrierIds" : [ 881 ],
"OriginId" : 56949,
"DestinationId" : 45348,
"DepartureDate" : "2021-12-06T00:00:00"
},
"QuoteDateTime" : "2021-06-06T19:16:00"
}, {
"QuoteId" : 7,
"MinPrice" : 2734,
"Direct" : true,
"OutboundLeg" : {
"CarrierIds" : [ 234 ],
"OriginId" : 56949,
"DestinationId" : 45348,
"DepartureDate" : "2021-06-19T00:00:00"
},
"QuoteDateTime" : "2021-06-06T20:26:00"
}, {
"QuoteId" : 8,
"MinPrice" : 2734,
"Direct" : true,
"OutboundLeg" : {
"CarrierIds" : [ 234 ],
"OriginId" : 56949,
"DestinationId" : 45348,
"DepartureDate" : "2021-08-02T00:00:00"
},
"QuoteDateTime" : "2021-06-06T20:27:00"
}, {
"QuoteId" : 9,
"MinPrice" : 2760,
"Direct" : true,
"OutboundLeg" : {
"CarrierIds" : [ 234 ],
"OriginId" : 56949,
"DestinationId" : 45348,
"DepartureDate" : "2021-07-02T00:00:00"
},
"QuoteDateTime" : "2021-06-07T06:11:00"
}, {
"QuoteId" : 10,
"MinPrice" : 4126,
"Direct" : true,
"OutboundLeg" : {
"CarrierIds" : [ 234 ],
"OriginId" : 56949,
"DestinationId" : 45348,
"DepartureDate" : "2021-12-15T00:00:00"
},
"QuoteDateTime" : "2021-06-06T19:16:00"
} ],
"Carriers" : [ {
"CarrierId" : 234,
"Name" : "Airlink"
}, {
"CarrierId" : 881,
"Name" : "British Airways"
} ],
"Places" : [ {
"Name" : "Cape Town",
"Type" : "Station",
"PlaceId" : 45348,
"IataCode" : "CPT",
"SkyscannerCode" : "CPT",
"CityName" : "Cape Town",
"CityId" : "CPTA",
"CountryName" : "South Africa"
}, {
"Name" : "Harare",
"Type" : "Station",
"PlaceId" : 56949,
"IataCode" : "HRE",
"SkyscannerCode" : "HRE",
"CityName" : "Harare",
"CityId" : "HREA",
"CountryName" : "Zimbabwe"
} ],
"Currencies" : [ {
"Code" : "ZAR",
"Symbol" : "R",
"ThousandsSeparator" : ",",
"DecimalSeparator" : ".",
"SymbolOnLeft" : true,
"SpaceBetweenAmountAndSymbol" : true,
"RoundingCoefficient" : 0,
"DecimalDigits" : 2
} ]
}
编辑 1：
我尝试了类似下面的代码，但我不明白如何使用将这些嵌套的 JSON 结构转换为数据帧：
import json
with open('myJson.json') as data_file:
data = json.load(data_file)
df = pd.json_normalize(data, 'Quotes', ["QuoteId", "MinPrice", "Direct", "DestinationId" , "DepartureDate", "QuoteDateTime"],
record_prefix='Quotes_')
我也发现了一个类似的问题here。
【问题讨论】：
-
我建议谷歌搜索“熊猫嵌套 json”
-
谢谢@AlexHall，我现在正在查看。看起来它可能正是解决方案。
-
提醒：如果
APIkey是一个真正的价值，那么它现在就被宠坏了！ -
@AlexHall，我认为这是我正在努力实施的解决方案。我已经简化了这个问题。
标签： python json pandas data-wrangling json-normalize