我有一个带有这种形式的输出的词典:
response['candles'][0:2]
[{'complete': True,
'mid': {'c': '0.91535', 'h': '0.91535', 'l': '0.91535', 'o': '0.91535'},
'time': '2002-05-06T21:00:00.000000000Z',
'volume': 1},
{'complete': True,
'mid': {'c': '0.90435', 'h': '0.90435', 'l': '0.90435', 'o': '0.90435'},
'time': '2002-05-07T21:00:00.000000000Z',
'volume': 1}]
我可以轻松创建一个看起来像这样的DataFrame:
res = pd.DataFrame(response['candles'])
complete mid time volume
0 True {'o': '0.91535', 'h': '0.91535', 'l': '0.91535... 2002-05-06T21:00:00.000000000Z 1
1 True {'o': '0.90435', 'h': '0.90435', 'l': '0.90435... 2002-05-07T21:00:00.000000000Z 1
我可以访问'mid'这样的dict项目:
response['candles'][0]['mid']['c']
'0.91535'
但是如何在每个'mid'项目的DataFrame中添加列,而不是在DataFrame中添加dict?我想要一个['mid'] ['o'],['mid'] ['h']的列,依此类推。
由于
答案 0 :(得分:1)
使用pandas.io.json.json_normalize
:
d = [{'complete': True,
'mid': {'c': '0.91535', 'h': '0.91535', 'l': '0.91535', 'o': '0.91535'},
'time': '2002-05-06T21:00:00.000000000Z',
'volume': 1},
{'complete': True,
'mid': {'c': '0.90435', 'h': '0.90435', 'l': '0.90435', 'o': '0.90435'},
'time': '2002-05-07T21:00:00.000000000Z',
'volume': 1}]
pd.io.json.json_normalize(d)
#complete mid.c mid.h mid.l mid.o time volume
#0 True 0.91535 0.91535 0.91535 0.91535 2002-05-06T21:00:00.000000000Z 1
#1 True 0.90435 0.90435 0.90435 0.90435 2002-05-07T21:00:00.000000000Z 1