从嵌套的json列表中展平Pandas DataFrame [英] Flatten Pandas DataFrame from nested json list

问题描述

也许有人可以帮助我.我试图将以下ist放到pandas数据框中:

perhaps somebody could help me. I tried to flat the following ist into a pandas dataframe:

[{u'_id': u'2',
  u'_index': u'list',
  u'_score': 1.4142135,
  u'_source': {u'name': u'name3'},
  u'_type': u'doc'},
 {u'_id': u'5',
  u'_index': u'list',
  u'_score': 1.4142135,
  u'_source': {u'dat': u'2016-12-12', u'name': u'name2'},
  u'_type': u'doc'},
 {u'_id': u'1',
  u'_index': u'list',
  u'_score': 1.4142135,
  u'_source': {u'name': u'name1'},
  u'_type': u'doc'}]

结果应如下所示:

|_id   | _index | _score | name | dat        | _type |
------------------------------------------------------
|1     |list    |1.4142..| name1| nan        | doc   |
|2     |list    |1.4142..| name3| nan        | doc   |
|3     |list    |1.4142..| name1| 2016-12-12 | doc   |

但是我试图做的所有事情都无法获得理想的结果. 我用了这样的东西:

But all I tried to do is not possible to get the desired result. I used something like this:

df = pd.concat(map(pd.DataFrame.from_dict, res['hits']['hits']), axis=1)['_source'].T

但是随后我松开了_source字段之外的类型. 我也尝试过与

But then I loose the types wich is outside the _source field. I also tried to work with

test = pd.DataFrame(list)
for index, row in test.iterrows():
  test.loc[index,'d'] = 

但是我不知道该如何使用_source字段并将其附加到原始数据框中.

But I have no idea how to come to the point to use the field _source and append it to the original data frame.

有人知道如何做到这一点并成为理想的结果吗?

Did somebody has an idea how to to that and become the desired outcome?

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