pandas.read_json failing on this input?

Question

I'm trying to convert a list of JSON objects to a pandas DataFrame. However, the JSON object has unquoted True/False, and None values, which appears to make read_json error out. Is there a way to make the pandas.read_json method handle Boolean and None values?

Updated with real code (my actual JSON I am getting from a web service, but I'm not able to post the real content):

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)

ValueError: Expected object or value

if I quote the Nones and Booleans it seems to work.

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)

Of course they are then strings rather than Booleans and NaNs

Updated with error message

---------------------------------------------------------------------------
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

So, if I treat the JSON as a python object rather than JSON I get a different error. This code

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)

yields

---------------------------------------------------------------------------
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