Normally if I have a json response from a API, I can load it as a dataframe using something like - pd.read_json(json)
but I'm noticed that some of the apis I call that only have a single item returned are not working. For example,a rest call returns:
{
"carbon_growth": 0.050962261831616916
}
then taking the response of a request to that endpoint and trying to cast it as a dataframe with the above command doesn't work and returns the following error:
/usr/local/lib/python3.7/dist-packages/py15rock/get.py in requestCompanyReturning(ticker, endpoint)
14 with httpx.Client() as client:
15 r = client.get(f'{config.api_endpoint}/company/{ticker}/{endpoint}', headers={'Authorization': f'{config.api_key}'}, timeout=timeout)
---> 16 df = pd.read_json(r.content)
17 return df
18
/usr/local/lib/python3.7/dist-packages/pandas/util/_decorators.py in wrapper(*args, **kwargs)
197 else:
198 kwargs[new_arg_name] = new_arg_value
--> 199 return func(*args, **kwargs)
200
201 return cast(F, wrapper)
/usr/local/lib/python3.7/dist-packages/pandas/util/_decorators.py in wrapper(*args, **kwargs)
294 )
295 warnings.warn(msg, FutureWarning, stacklevel=stacklevel)
--> 296 return func(*args, **kwargs)
297
298 return wrapper
/usr/local/lib/python3.7/dist-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, nrows)
616 return json_reader
617
--> 618 result = json_reader.read()
619 if should_close:
620 filepath_or_buffer.close()
/usr/local/lib/python3.7/dist-packages/pandas/io/json/_json.py in read(self)
753 obj = self._get_object_parser(self._combine_lines(data))
754 else:
--> 755 obj = self._get_object_parser(self.data)
756 self.close()
757 return obj
/usr/local/lib/python3.7/dist-packages/pandas/io/json/_json.py in _get_object_parser(self, json)
775 obj = None
776 if typ == "frame":
--> 777 obj = FrameParser(json, **kwargs).parse()
778
779 if typ == "series" or obj is None:
/usr/local/lib/python3.7/dist-packages/pandas/io/json/_json.py in parse(self)
884
885 else:
--> 886 self._parse_no_numpy()
887
888 if self.obj is None:
/usr/local/lib/python3.7/dist-packages/pandas/io/json/_json.py in _parse_no_numpy(self)
1117 if orient == "columns":
1118 self.obj = DataFrame(
-> 1119 loads(json, precise_float=self.precise_float), dtype=None
1120 )
1121 elif orient == "split":
/usr/local/lib/python3.7/dist-packages/pandas/core/frame.py in __init__(self, data, index, columns, dtype, copy)
466
467 elif isinstance(data, dict):
--> 468 mgr = init_dict(data, index, columns, dtype=dtype)
469 elif isinstance(data, ma.MaskedArray):
470 import numpy.ma.mrecords as mrecords
/usr/local/lib/python3.7/dist-packages/pandas/core/internals/construction.py in init_dict(data, index, columns, dtype)
281 arr if not is_datetime64tz_dtype(arr) else arr.copy() for arr in arrays
282 ]
--> 283 return arrays_to_mgr(arrays, data_names, index, columns, dtype=dtype)
284
285
/usr/local/lib/python3.7/dist-packages/pandas/core/internals/construction.py in arrays_to_mgr(arrays, arr_names, index, columns, dtype, verify_integrity)
76 # figure out the index, if necessary
77 if index is None:
---> 78 index = extract_index(arrays)
79 else:
80 index = ensure_index(index)
/usr/local/lib/python3.7/dist-packages/pandas/core/internals/construction.py in extract_index(data)
385
386 if not indexes and not raw_lengths:
--> 387 raise ValueError("If using all scalar values, you must pass an index")
388
389 if have_series:
ValueError: If using all scalar values, you must pass an index
Is there something I can do to access responses like above? It seems to work when the response is multiple rows.
