Stack trace when loading category 33845

[boreshkinai]

fr = Fred(api_key=api_key,response_type='df')
fr.category.series(33845, params={'limit':1000, 'offset': 0})

---

TypeError Traceback (most recent call last)
/usr/local/lib/python3.7/dist-packages/pandas/core/tools/datetimes.py in _convert_listlike(arg, box, format, name, tz)
376 try:
--> 377 values, tz = conversion.datetime_to_datetime64(arg)
378 return DatetimeIndex._simple_new(values, name=name, tz=tz)

pandas/_libs/tslibs/conversion.pyx in pandas._libs.tslibs.conversion.datetime_to_datetime64()

TypeError: Unrecognized value type: <class 'str'>

During handling of the above exception, another exception occurred:

OutOfBoundsDatetime Traceback (most recent call last)
/tmp/ipykernel_333/1514929282.py in
1 fr = get_fred_api()
2
----> 3 fr.category.series(33845, params={'limit':RESPONSE_LIMIT, 'offset': 0})

/usr/local/lib/python3.7/dist-packages/fred/utils/init.py in _wrapped(*args, **kwargs)
15 if p in kwargs:
16 params[p] = kwargs.pop(p)
---> 17 return func(*args,params=params,**kwargs)
18 return _wrapped
19 return _wrapper

/usr/local/lib/python3.7/dist-packages/fred/clients/categories.py in series(self, category_id, response_type, params)
93 response_type = response_type if response_type else self.response_type
94 if response_type != 'xml': params['file_type'] = 'json'
---> 95 response = _get_request(self.url_root,self.api_key,path,response_type,params)
96 return response
97

/usr/local/lib/python3.7/dist-packages/fred/helpers/init.py in _get_request(url_root, api_key, path, response_type, params)
115 url = _url_builder(url_root,api_key,path,params)
116 content = _fetch(url)
--> 117 response = _dispatch(response_type)(content)
118 return response

/usr/local/lib/python3.7/dist-packages/fred/helpers/init.py in _data_frame(content)
56 key = [x for x in response.keys() if x in c.response_data][0]
57 frame = DataFrame(response[key])
---> 58 final_frame = _convert(frame)
59 return final_frame
60

/usr/local/lib/python3.7/dist-packages/fred/helpers/init.py in _convert(frame)
37 for column in frame:
38 if column in c.dates:
---> 39 frame[column] = frame[column].astype('datetime64')
40 return frame
41

/usr/local/lib/python3.7/dist-packages/pandas/util/_decorators.py in wrapper(*args, **kwargs)
176 else:
177 kwargs[new_arg_name] = new_arg_value
--> 178 return func(*args, **kwargs)
179 return wrapper
180 return _deprecate_kwarg

/usr/local/lib/python3.7/dist-packages/pandas/core/generic.py in astype(self, dtype, copy, errors, **kwargs)
4999 # else, only a single dtype is given
5000 new_data = self._data.astype(dtype=dtype, copy=copy, errors=errors,
-> 5001 **kwargs)
5002 return self._constructor(new_data).finalize(self)
5003

/usr/local/lib/python3.7/dist-packages/pandas/core/internals.py in astype(self, dtype, **kwargs)
3712
3713 def astype(self, dtype, **kwargs):
-> 3714 return self.apply('astype', dtype=dtype, **kwargs)
3715
3716 def convert(self, **kwargs):

/usr/local/lib/python3.7/dist-packages/pandas/core/internals.py in apply(self, f, axes, filter, do_integrity_check, consolidate, **kwargs)
3579
3580 kwargs['mgr'] = self
-> 3581 applied = getattr(b, f)(**kwargs)
3582 result_blocks = _extend_blocks(applied, result_blocks)
3583

/usr/local/lib/python3.7/dist-packages/pandas/core/internals.py in astype(self, dtype, copy, errors, values, **kwargs)
573 def astype(self, dtype, copy=False, errors='raise', values=None, **kwargs):
574 return self._astype(dtype, copy=copy, errors=errors, values=values,
--> 575 **kwargs)
576
577 def _astype(self, dtype, copy=False, errors='raise', values=None,

/usr/local/lib/python3.7/dist-packages/pandas/core/internals.py in _astype(self, dtype, copy, errors, values, klass, mgr, **kwargs)
662
663 # _astype_nansafe works fine with 1-d only
--> 664 values = astype_nansafe(values.ravel(), dtype, copy=True)
665 values = values.reshape(self.shape)
666

/usr/local/lib/python3.7/dist-packages/pandas/core/dtypes/cast.py in astype_nansafe(arr, dtype, copy)
714 elif is_datetime64_dtype(dtype):
715 from pandas import to_datetime
--> 716 return astype_nansafe(to_datetime(arr).values, dtype, copy=copy)
717 elif is_timedelta64_dtype(dtype):
718 from pandas import to_timedelta

/usr/local/lib/python3.7/dist-packages/pandas/core/tools/datetimes.py in to_datetime(arg, errors, dayfirst, yearfirst, utc, box, format, exact, unit, infer_datetime_format, origin, cache)
465 result = _convert_and_box_cache(arg, cache_array, box, errors)
466 else:
--> 467 result = _convert_listlike(arg, box, format)
468 else:
469 result = _convert_listlike(np.array([arg]), box, format)[0]

/usr/local/lib/python3.7/dist-packages/pandas/core/tools/datetimes.py in _convert_listlike(arg, box, format, name, tz)
378 return DatetimeIndex._simple_new(values, name=name, tz=tz)
379 except (ValueError, TypeError):
--> 380 raise e
381
382 if arg is None:

/usr/local/lib/python3.7/dist-packages/pandas/core/tools/datetimes.py in _convert_listlike(arg, box, format, name, tz)
366 dayfirst=dayfirst,
367 yearfirst=yearfirst,
--> 368 require_iso8601=require_iso8601
369 )
370

pandas/_libs/tslib.pyx in pandas._libs.tslib.array_to_datetime()

pandas/_libs/tslib.pyx in pandas._libs.tslib.array_to_datetime()

pandas/_libs/tslib.pyx in pandas._libs.tslib.array_to_datetime()

pandas/_libs/tslib.pyx in pandas._libs.tslib.array_to_datetime()

pandas/_libs/tslibs/np_datetime.pyx in pandas._libs.tslibs.np_datetime.check_dts_bounds()

OutOfBoundsDatetime: Out of bounds nanosecond timestamp: 1270-01-01 00:00:00

[boreshkinai]

The issue is here:

/usr/local/lib/python3.7/dist-packages/fred/helpers/init.py in _convert(frame)
37 for column in frame:
38 if column in c.dates:
---> 39 frame[column] = frame[column].astype('datetime64')
40 return frame
41

I think the conversion could be best done using safe method such as

frame[column] = pd.to_datetime(frame[column], errors = 'coerce')