read_json can't import own exported data with orient=table

import pandas
pd = pandas.DataFrame([["Arr","alpha", [1,2,3,4]],["Bee", "Beta", [10,20,30,40]]], index = [["A", "B"], ["Null", "Eins"]], columns = ["Aussprache", "Griechisch", "Args"])

: print(pd)
       Aussprache Griechisch              Args
A Null        Arr      alpha      [1, 2, 3, 4]
B Eins        Bee       Beta  [10, 20, 30, 40]

pd.to_json("test.json", orient = "table")
pandas.read_json("test.json", orient="table")

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-66-a171b349d78d> in <module>()
----> 1 pandas.read_json("test.json", orient="table")

/usr/lib/python3.6/site-packages/pandas/io/json/json.py in read_json(path_or_buf, orient, typ, dtype, convert_axes, convert_dates, keep_default_dates, numpy, precise_float, date_unit, encoding, lines, chunksize, compression)
    364         return json_reader
    365
--> 366     return json_reader.read()
    367
    368

/usr/lib/python3.6/site-packages/pandas/io/json/json.py in read(self)
    463             )
    464         else:
--> 465             obj = self._get_object_parser(self.data)
    466         self.close()
    467         return obj

/usr/lib/python3.6/site-packages/pandas/io/json/json.py in _get_object_parser(self, json)
    480         obj = None
    481         if typ == 'frame':
--> 482             obj = FrameParser(json, **kwargs).parse()
    483
    484         if typ == 'series' or obj is None:

/usr/lib/python3.6/site-packages/pandas/io/json/json.py in parse(self)
    572
    573         else:
--> 574             self._parse_no_numpy()
    575
    576         if self.obj is None:

/usr/lib/python3.6/site-packages/pandas/io/json/json.py in _parse_no_numpy(self)
    802         else:
    803             self.obj = DataFrame(
--> 804                 loads(json, precise_float=self.precise_float), dtype=None)
    805
    806     def _process_converter(self, f, filt=None):

/usr/lib/python3.6/site-packages/pandas/core/frame.py in __init__(self, data, index, columns, dtype, copy)
    328                                  dtype=dtype, copy=copy)
    329         elif isinstance(data, dict):
--> 330             mgr = self._init_dict(data, index, columns, dtype=dtype)
    331         elif isinstance(data, ma.MaskedArray):
    332             import numpy.ma.mrecords as mrecords

/usr/lib/python3.6/site-packages/pandas/core/frame.py in _init_dict(self, data, index, columns, dtype)
    459             arrays = [data[k] for k in keys]
    460
--> 461         return _arrays_to_mgr(arrays, data_names, index, columns, dtype=dtype)
    462
    463     def _init_ndarray(self, values, index, columns, dtype=None, copy=False):

/usr/lib/python3.6/site-packages/pandas/core/frame.py in _arrays_to_mgr(arrays, arr_names, index, columns, dtype)
   6128     # figure out the index, if necessary
   6129     if index is None:
-> 6130         index = extract_index(arrays)
   6131     else:
   6132         index = _ensure_index(index)

/usr/lib/python3.6/site-packages/pandas/core/frame.py in extract_index(data)
   6179
   6180             if have_dicts:
-> 6181                 raise ValueError('Mixing dicts with non-Series may lead to '
   6182                                  'ambiguous ordering.')
   6183

ValueError: Mixing dicts with non-Series may lead to ambiguous ordering.

Problem description

test.json looks like:

{"schema": {"fields":[{"name":"level_0","type":"string"},{"name":"level_1","type":"string"},{"name":"Aussprache","type":"string"},{"name":"Griechisch","type":"string"},{"name":"Args","type":"string"}],"primaryKey":["level_0","level_1"],"pandas_version":"0.20.0"}, "data": [{"level_0":"A","level_1":"Null","Aussprache":"Arr","Griechisch":"alpha","Args":[1,2,3,4]},{"level_0":"B","level_1":"Eins","Aussprache":"Bee","Griechisch":"Beta","Args":[10,20,30,40]}]}

Output of pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.14.7-1-ARCH
machine: x86_64
processor:
byteorder: little
LC_ALL: None
LANG: de_DE.UTF-8
LOCALE: de_DE.UTF-8

pandas: 0.21.0
pytest: None
pip: 9.0.1
setuptools: 38.2.4
Cython: 0.27.3
numpy: 1.13.3
scipy: 1.0.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: 1.6.5
patsy: None
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.1.1
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.6.0
html5lib: None
sqlalchemy: 1.1.15
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

[jreback]

FYI don’t use pd as a variable name, when the common import for pandas is pd

In [26]: df = pd.DataFrame([["Arr","alpha", [1,2,3,4]],["Bee", "Beta", [10,20,30,40]]], index = [["A", "B"], ["Null", "Eins"]], columns = ["Aussprache", "Griechisch", "Args"])

In [27]: df
Out[27]: 
       Aussprache Griechisch              Args
A Null        Arr      alpha      [1, 2, 3, 4]
B Eins        Bee       Beta  [10, 20, 30, 40]

I don’t we have any guarantees when you embed lists inside a field and try to export to json. Further I don’t think orient='table' is actually reversible.

[jreback]

records works just fine here.

In [34]: pd.read_json(df.to_json(orient='records'), orient='records')
Out[34]: 
               Args Aussprache Griechisch
0      [1, 2, 3, 4]        Arr      alpha
1  [10, 20, 30, 40]        Bee       Beta