Question

我有这个简短版本的ADSB json数据，并希望将其转换为DataFrame列，如Icao，Alt，Lat，Long，Spd，Cou ......

在Alperen告诉我这样做之后

df = pd.read_json('2016-06-20-2359Z.json', lines=True),

我可以将其加载到DataFrame中。但是，df.acList是

[{'Id': 10537990, 'Rcvr': 1, 'HasSig': False, ...
Name: acList, dtype: object

如何获取Icao，Alt，Lat，Long，Spd，Cou数据？

 "src":1,
   "feeds":[  
      {  
         "id":1,
         "name":"ADSBexchange.com",
         "polarPlot":false
      }
   ],
   "srcFeed":1,
   "showSil":true,
   "showFlg":true,
   "showPic":true,
   "flgH":20,
   "flgW":85,
   "acList":[  
      {  
         "Id":11281748,
         "Rcvr":1,
         "HasSig":false,
         "Icao":"AC2554",
         "Bad":false,
         "Reg":"N882AS",
         "FSeen":"\/Date(1466467166951)\/",
         "TSecs":3,
         "CMsgs":1,
         "AltT":0,
         "Tisb":false,
         "TrkH":false,
         "Type":"CRJ2",
         "Mdl":"2001 
BOMBARDIER INC 
 CL-600-2B19",
         "Man":"Bombardier",
         "CNum":"7503",
         "Op":"EXPRESSJET AIRLINES INC - ATLANTA, GA",
         "OpIcao":"ASQ",
         "Sqk":"",
         "VsiT":0,
         "WTC":2,
         "Species":1,
         "Engines":"2",
         "EngType":3,
         "EngMount":1,
         "Mil":false,
         "Cou":"United States",
         "HasPic":false,
         "Interested":false,
         "FlightsCount":0,
         "Gnd":false,
         "SpdTyp":0,
         "CallSus":false,
         "TT":"a",
         "Trt":1,
         "Year":"2001"
      },
      {  
         "Id":11402205,
         "Rcvr":1,
         "HasSig":true,
         "Sig":110,
         "Icao":"ADFBDD",
         "Bad":false,
         "FSeen":"\/Date(1466391940977)\/",
         "TSecs":75229,
         "CMsgs":35445,
         "Alt":8025,
         "GAlt":8025,
         "AltT":0,
         "Call":"TEST1234",
         "Tisb":false,
         "TrkH":false,
         "Sqk":"0262",
         "Help":false,
         "VsiT":0,
         "WTC":0,
         "Species":0,
         "EngType":0,
         "EngMount":0,
         "Mil":true,
         "Cou":"United States",
         "HasPic":false,
         "Interested":false,
         "FlightsCount":0,
         "Gnd":true,
         "SpdTyp":0,
         "CallSus":false,
         "TT":"a",
         "Trt":1
      }
   ],
   "totalAc":4231,
   "lastDv":"636019887431643594",
   "shtTrlSec":61,
   "stm":1466467170029
}

Answer 1

如果您已将数据放在pandas DataFrame的acList列中，只需执行以下操作：

import pandas as pd
pd.io.json.json_normalize(df.acList[0])

Alt AltT    Bad CMsgs   CNum    Call    CallSus Cou EngMount    EngType ... Sqk TSecs   TT  Tisb    TrkH    Trt Type    VsiT    WTC Year
0   NaN 0   False   1   7503    NaN False   United States   1   3   ...     3   a   False   False   1   CRJ2    0   2   2001
1   8025.0  0   False   35445   NaN TEST1234    False   United States   0   0   ... 0262    75229   a   False   False   1   NaN 0   0   NaN

Answer 2

@Sergey的答案为我解决了这个问题，但是我遇到了问题，因为数据框列中的json保留为字符串而不是对象。我必须添加映射列的附加步骤：

import json
import pandas as pd
pd.io.json.json_normalize(df.acList.apply(json.loads))

Answer 3

我尚无法对ThinkBonobo的答案发表评论，但是如果该列中的JSON并非完全是字典，那么您可以继续进行.apply直到完成。所以就我而言

import json
import pandas as pd

json_normalize(
    df
    .theColumnWithJson
    .apply(json.loads)
    .apply(lambda x: x[0]) # the inner JSON is list with the dictionary as the only item
)

Answer 4

自pandas 1.0起，json_normalize在顶级名称空间中可用。因此使用：

type B = {
    key: "str";
    type: string;
} | {
    key: "num";
    type: number;
}

Answer 5

在我的情况下，我缺少一些值（None），然后创建了一个更具体的代码，该代码在创建新值之后也会删除原始列：

for prefix in ['column1', 'column2']:
    df_temp = df[prefix].apply(lambda x: {} if pd.isna(x) else x)
    df_temp = pd.io.json.json_normalize(df_temp)
    df_temp = df_temp.add_prefix(prefix + '_')
    df.drop([prefix], axis=1, inplace=True)
    df = pd.concat([df, df_temp], axis = 1, sort=False)

如何将pandas列中的JSON数据转换为新列

5 个答案: