json_normalize会产生令人困惑的KeyError [英] json_normalize produces confusing KeyError

问题描述

我正在尝试将嵌套的json转换为熊猫数据帧。我一直在使用json_normalize成功，直到我遇到某个json。我已经做了一个较小的版本来重新创建问题。

 从pandas.io.json import json_normalize 
 
 json = [{events：[{schedule：{date：2015-08-27，
location：{building：BDC floor：5}，
ID：815}，
group：A}，
 {schedule：{date 27，
location：{building：BDC，floor：5}，
ID：816}，
group：A} ]}] 
  

我跑了：

  json_normalize（JSON [0]， '事件'，[[ '日程'， '日期']，[ '日程'， '位置'， '建筑']，[ '日程'， 'location'，'floor']]）
  

希望看到这样的东西：

  ID组schedule.date schedule.location.building schedule.location.floor 
'815''A''2015-08- 27BDC'5 
'816''A''2015-08-27''BDC '5 
  

但是我收到这个错误：

在[2]中：json_normalize（json [0]，'events'，[['schedule'，'date']，['schedule'，'location'，'building ']，['schedule'，'location'，'floor']]）
---------------------------- -----------------------------------------------
KeyError Traceback（最近的最后一次调用）
< ipython-input-2-b588a9e3ef1d>在< module>（）
----> 1 json_normalize（json_normalize（json [0]，'events'，[['schedule'，'date']，['schedule'，'location'，'building']，['schedule'，'location'，'floor' ]）

/Users/logan/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pandas/io/json.pyc在json_normalize（data，record_path，meta，meta_prefix ，record_prefix）
739 records.extend（recs）
740
- > 741 _recursive_extract（data，record_path，{}，level = 0）
742
743 result = DataFrame（records）

/ Users / logan / Library / Enthought / Canopy_64bit / User /lib/python2.7/site-packages/pandas/io/json.pyc在_recursive_extract（data，path，seen_meta，level）
734 meta_val = seen_meta [key]
735 else：
- > 736 meta_val = _pull_field（obj，val [level：]）
737 meta_vals [key] .append（meta_val）
738

/ Users / logan / Library / Enthought / Canopy_64bit /User/lib/python2.7/site-packages/pandas/io/json.pyc in _pull_field（js，spec）
674 if isinstance（spec，list）：
675 for field in spec：
- > 676 result = result [field]
677 else：
678 result = result [spec]

KeyError：'schedule'
/ pre>

解决方案

在这种情况下，我想你只是使用这个：

 在[57]中：json_normalize（data [0] ['events']）
 Out [57]：
 group schedule.ID schedule。日期schedule.location.building \ 
 0 A 815 2015-08-27 BDC 
 1 A 816 2015-08-27 BDC 
 
 schedule.location.floor 
 0 5 
 1 5 
  

meta 路径（ [['schedule'，'date'] ...] ）用于指定与记录相同的嵌套级别的数据，即在与事件相同。它不像 json_normalize 特别适用嵌套列表的列表，所以如果实际数据复杂得多，您可能需要进行一些手动整形。

I'm trying to convert a nested json to a pandas dataframe. I've been using json_normalize with success until I came across a certain json. I've made a smaller version of it to re-create the problem.

from pandas.io.json import json_normalize

json=[{"events": [{"schedule": {"date": "2015-08-27",
     "location": {"building": "BDC", "floor": 5},
     "ID": 815},
    "group": "A"},
   {"schedule": {"date": "2015-08-27",
     "location": {"building": "BDC", "floor": 5},
 "ID": 816},
"group": "A"}]}]

I ran:

json_normalize(json[0],'events',[['schedule','date'],['schedule','location','building'],['schedule','location','floor']])

Expecting to see something like this:

ID      group   schedule.date   schedule.location.building schedule.location.floor  
'815'   'A'     '2015-08-27'            'BDC'                       5
'816'   'A'     '2015-08-27'            'BDC'                       5

But instead I got this error:

In [2]: json_normalize(json[0],'events',[['schedule','date'],['schedule','location','building'],['schedule','location','floor']])
---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-2-b588a9e3ef1d> in <module>()
----> 1 json_normalize(json[0],'events',[['schedule','date'],['schedule','location','building'],['schedule','location','floor']])

/Users/logan/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pandas/io/json.pyc in json_normalize(data, record_path, meta, meta_prefix, record_prefix)
    739                 records.extend(recs)
    740
--> 741     _recursive_extract(data, record_path, {}, level=0)
    742
    743     result = DataFrame(records)

/Users/logan/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pandas/io/json.pyc in _recursive_extract(data, path, seen_meta, level)
    734                         meta_val = seen_meta[key]
    735                     else:
--> 736                         meta_val = _pull_field(obj, val[level:])
    737                     meta_vals[key].append(meta_val)
    738

/Users/logan/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/pandas/io/json.pyc in _pull_field(js, spec)
    674         if isinstance(spec, list):
    675             for field in spec:
--> 676                 result = result[field]
    677         else:
    678             result = result[spec]

KeyError: 'schedule'

解决方案

In this case, I think you'd just use this:

In [57]: json_normalize(data[0]['events'])
Out[57]: 
  group  schedule.ID schedule.date schedule.location.building  \
0     A          815    2015-08-27                        BDC   
1     A          816    2015-08-27                        BDC   

   schedule.location.floor  
0                        5  
1                        5  

The meta paths ([['schedule','date']...]) are for specifying data at the same level of nesting as your records, i.e. at the same level as 'events'. It doesn't look like json_normalize handles dicts with nested lists particularly well, so you may need to do some manual reshaping if your actual data is much more complicated.

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