Question

我正在尝试将JSON对象列表转换为pandas DataFrame。但是，JSON对象具有不带引号的True / False和None值，这似乎使read_json错误输出。有没有办法让pandas.read_json方法处理布尔值和无值？

更新了真实代码

import pandas as pd
x = '[{"A": "some text","B": True,"C":7},{"A": "more text","B":False,"C":8},{"A":None,"B":False,"C":9}]'
pd.read_json(x)

如果我引用Nones和Booleans，它似乎有效。

import pandas as pd
x = '[{"A": "some text","B": "True","C":7},{"A": "more text","B":"False","C":8},{"A":"None","B":"False","C":9}]'
pd.read_json(x)

当然，他们是字符串，而不是布尔和NaNs

我从网络服务获得的真正的JSON，但我无法发布真实的内容。

更新了错误消息

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-42-c251da58cd34> in <module>()
      1 import pandas as pd
      2 x = '[{"A": "some text","B": True,"C":7},{"A": "more text","B":False,"C":8},{"A":None,"B":False,"C":9}]'
----> 3 pd.read_json(x)

C:\Users\Chris\AppData\Local\Continuum\Miniconda3\lib\site-packages\pandas\io\json.py in read_json(path_or_buf, orient, typ, dtype, convert_axes, convert_dates, keep_default_dates, numpy, precise_float, date_unit)
    196         obj = FrameParser(json, orient, dtype, convert_axes, convert_dates,
    197                           keep_default_dates, numpy, precise_float,
--> 198                           date_unit).parse()
    199 
    200     if typ == 'series' or obj is None:

C:\Users\Chris\AppData\Local\Continuum\Miniconda3\lib\site-packages\pandas\io\json.py in parse(self)
    264 
    265         else:
--> 266             self._parse_no_numpy()
    267 
    268         if self.obj is None:

C:\Users\Chris\AppData\Local\Continuum\Miniconda3\lib\site-packages\pandas\io\json.py in _parse_no_numpy(self)
    481         if orient == "columns":
    482             self.obj = DataFrame(
--> 483                 loads(json, precise_float=self.precise_float), dtype=None)
    484         elif orient == "split":
    485             decoded = dict((str(k), v)

ValueError: Expected object or value

因此，如果我将JSON视为python对象而不是JSON，我会得到不同的错误。这段代码

x =   [{"A": "some text","B": "True","C":7},{"A": "more text","B":"False","C":8},{"A":"None","B":"False","C":9}]
pd.read_json(x)

产量

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-59-076202b1f4ce> in <module>()
      1 x =   [{"A": "some text","B": True,"C":7},{"A": "more text","B":False,"C":8},{"A":"None","B":False,"C":9}]
----> 2 pd.read_json(x)

C:\Users\Chris\AppData\Local\Continuum\Miniconda3\lib\site-packages\pandas\io\json.py in read_json(path_or_buf, orient, typ, dtype, convert_axes, convert_dates, keep_default_dates, numpy, precise_float, date_unit)
    196         obj = FrameParser(json, orient, dtype, convert_axes, convert_dates,
    197                           keep_default_dates, numpy, precise_float,
--> 198                           date_unit).parse()
    199 
    200     if typ == 'series' or obj is None:

C:\Users\Chris\AppData\Local\Continuum\Miniconda3\lib\site-packages\pandas\io\json.py in parse(self)
    264 
    265         else:
--> 266             self._parse_no_numpy()
    267 
    268         if self.obj is None:

C:\Users\Chris\AppData\Local\Continuum\Miniconda3\lib\site-packages\pandas\io\json.py in _parse_no_numpy(self)
    481         if orient == "columns":
    482             self.obj = DataFrame(
--> 483                 loads(json, precise_float=self.precise_float), dtype=None)
    484         elif orient == "split":
    485             decoded = dict((str(k), v)

TypeError: Expected String or Unicode

Answer 1

x = [{"A": "some text","B": True,"C":7},{"A": "more text","B":False,"C":8},{"A":None,"B":False,"C":9}]
pd.read_json(json.dumps(x))
    A   B   C
0   some text   True    7
1   more text   False   8
2   None    False   9

pandas.read_json，带布尔值和无

1 个答案: