read_json can't import own exported data with orient=table · Issue #18912 · pandas-dev/pandas (original) (raw)
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) in () ----> 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