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I can't seem to find a fix for the "ValueError: Unknown subheader signature" raised while reading sas file using pd.read_sas?

I am trying to load a sasbdat file in python using pd.read_sas() and I fail to load the data due to the below error.
ValueError Traceback (most recent call last)
<ipython-input-148-64f915da8256> in <module>
----> 1 df_sas = pd.read_sas('input_sasfile.sas7bdat', format='sas7bdat')
~\.conda\envs\overloaded-new\lib\site-packages\pandas\io\sas\sasreader.py in read_sas(filepath_or_buffer, format, index, encoding, chunksize, iterator)
121
122 reader = SAS7BDATReader(
--> 123 filepath_or_buffer, index=index, encoding=encoding, chunksize=chunksize
124 )
125 else:
~\.conda\envs\overloaded-new\lib\site-packages\pandas\io\sas\sas7bdat.py in __init__(self, path_or_buf, index, convert_dates, blank_missing, chunksize, encoding, convert_text, convert_header_text)
144
145 self._get_properties()
--> 146 self._parse_metadata()
147
148 def column_data_lengths(self):
~\.conda\envs\overloaded-new\lib\site-packages\pandas\io\sas\sas7bdat.py in _parse_metadata(self)
349 self.close()
350 raise ValueError("Failed to read a meta data page from the SAS file.")
--> 351 done = self._process_page_meta()
352
353 def _process_page_meta(self):
~\.conda\envs\overloaded-new\lib\site-packages\pandas\io\sas\sas7bdat.py in _process_page_meta(self)
355 pt = [const.page_meta_type, const.page_amd_type] + const.page_mix_types
356 if self._current_page_type in pt:
--> 357 self._process_page_metadata()
358 is_data_page = self._current_page_type & const.page_data_type
359 is_mix_page = self._current_page_type in const.page_mix_types
~\.conda\envs\overloaded-new\lib\site-packages\pandas\io\sas\sas7bdat.py in _process_page_metadata(self)
388 subheader_signature = self._read_subheader_signature(pointer.offset)
389 subheader_index = self._get_subheader_index(
--> 390 subheader_signature, pointer.compression, pointer.ptype
391 )
392 self._process_subheader(subheader_index, pointer)
~\.conda\envs\overloaded-new\lib\site-packages\pandas\io\sas\sas7bdat.py in _get_subheader_index(self, signature, compression, ptype)
401 else:
402 self.close()
--> 403 raise ValueError("Unknown subheader signature")
404 return index
405
ValueError: Unknown subheader signature
Though I found relevant github issue (https://github.com/pandas-dev/pandas/issues/24794), but it was closed because the issue got resolved by updating the pandas.
Any help is greatly appreciated.

appending json files in python

I am trying to append some json files in python. I have the following code. It seems right. However, I am getting an error.
The code is as follows.
import pandas as pd
df1=pd.DataFrame()
for i in range(0,49):
df = pd.read_json ('/media/michael/extHDD/Kaggle/DeepFAke/DF_all/metadata{}.json'.format(i))
df1.append(df.T)
The error is as follows.
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-76-ddb355627155> in <module>
3 df1=pd.DataFrame()
4 for i in range(0,49):
----> 5 df = pd.read_json ('/media/michael/extHDD/Kaggle/DeepFAke/DF_all/metadata{}.json'.format(i))
6 df1.append(df.T)
~/myenv/lib/python3.5/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)
590 return json_reader
591
--> 592 result = json_reader.read()
593 if should_close:
594 try:
~/myenv/lib/python3.5/site-packages/pandas/io/json/_json.py in read(self)
715 obj = self._get_object_parser(self._combine_lines(data.split("\n")))
716 else:
--> 717 obj = self._get_object_parser(self.data)
718 self.close()
719 return obj
~/myenv/lib/python3.5/site-packages/pandas/io/json/_json.py in _get_object_parser(self, json)
737 obj = None
738 if typ == "frame":
--> 739 obj = FrameParser(json, **kwargs).parse()
740
741 if typ == "series" or obj is None:
~/myenv/lib/python3.5/site-packages/pandas/io/json/_json.py in parse(self)
847
848 else:
--> 849 self._parse_no_numpy()
850
851 if self.obj is None:
~/myenv/lib/python3.5/site-packages/pandas/io/json/_json.py in _parse_no_numpy(self)
1091 if orient == "columns":
1092 self.obj = DataFrame(
-> 1093 loads(json, precise_float=self.precise_float), dtype=None
1094 )
1095 elif orient == "split":
ValueError: Expected object or value
The code works when I do it for each file individually. Would anyone be able to help me regarding this.
Thanks & Best Regards
Michael

The error occurs on a df = pd.read_json (...) line. It is likely that one of the file is non existent or incorrect. My advice is to use a try catch to identify it:
for i in range(0,49):
try:
df = pd.read_json ('/media/michael/extHDD/Kaggle/DeepFAke/DF_all/metadata{}.json'.format(i))
except:
print('Error on iteration', i, ', file',
'/media/michael/extHDD/Kaggle/DeepFAke/DF_all/metadata{}.json'.format(i))
raise
df1.append(df.T)
Catching any exception is normally bad practice because it can hide truely abnormal conditions like an IO or memory error. That is the reason why I re-raise the original exception in above code.

Error when using pandas dataframe in R cell, in rpy2, Jupyter Notebook

I want to use ggplot2 within Jupyter Notebook. However, when I try to make an R magic cell and introduce a variable, I get an error.
Here is the code (one paragraph indicates one cell):
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import rpy2
%matplotlib inline
from rpy2.robjects import pandas2ri
pandas2ri.activate()
%load_ext rpy2.ipython
%%R
library(ggplot2)
data = pd.read_csv('train_titanic.csv')
%%R -i data -w 900 -h 480 -u px
With this last cell, I get the following error (incl traceback):
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/robjects/pandas2ri.py in py2rpy_pandasdataframe(obj)
54 try:
---> 55 od[name] = conversion.py2rpy(values)
56 except Exception as e:
~/anaconda3/envs/catenv/lib/python3.7/functools.py in wrapper(*args, **kw)
839
--> 840 return dispatch(args[0].__class__)(*args, **kw)
841
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/robjects/pandas2ri.py in py2rpy_pandasseries(obj)
125 if type(x) is not homogeneous_type:
--> 126 raise ValueError('Series can only be of one type, or None.')
127 # TODO: Could this be merged with obj.type.name == 'O' case above ?
ValueError: Series can only be of one type, or None.
During handling of the above exception, another exception occurred:
TypeError Traceback (most recent call last)
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/rinterface_lib/sexp.py in from_object(cls, obj)
367 try:
--> 368 mv = memoryview(obj)
369 res = cls.from_memoryview(mv)
TypeError: memoryview: a bytes-like object is required, not 'Series'
During handling of the above exception, another exception occurred:
AttributeError Traceback (most recent call last)
<ipython-input-14-75e210679e4a> in <module>
----> 1 get_ipython().run_cell_magic('R', '-i data -w 900 -h 480 -u px', '\n\n')
~/anaconda3/envs/catenv/lib/python3.7/site-packages/IPython/core/interactiveshell.py in run_cell_magic(self, magic_name, line, cell)
2360 with self.builtin_trap:
2361 args = (magic_arg_s, cell)
-> 2362 result = fn(*args, **kwargs)
2363 return result
2364
</home/morgan/anaconda3/envs/catenv/lib/python3.7/site-packages/decorator.py:decorator-gen-130> in R(self, line, cell, local_ns)
~/anaconda3/envs/catenv/lib/python3.7/site-packages/IPython/core/magic.py in <lambda>(f, *a, **k)
185 # but it's overkill for just that one bit of state.
186 def magic_deco(arg):
--> 187 call = lambda f, *a, **k: f(*a, **k)
188
189 if callable(arg):
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/ipython/rmagic.py in R(self, line, cell, local_ns)
721 raise NameError("name '%s' is not defined" % input)
722 with localconverter(converter) as cv:
--> 723 ro.r.assign(input, val)
724
725 tmpd = self.setup_graphics(args)
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/robjects/functions.py in __call__(self, *args, **kwargs)
190 kwargs[r_k] = v
191 return (super(SignatureTranslatedFunction, self)
--> 192 .__call__(*args, **kwargs))
193
194
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/robjects/functions.py in __call__(self, *args, **kwargs)
111
112 def __call__(self, *args, **kwargs):
--> 113 new_args = [conversion.py2rpy(a) for a in args]
114 new_kwargs = {}
115 for k, v in kwargs.items():
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/robjects/functions.py in <listcomp>(.0)
111
112 def __call__(self, *args, **kwargs):
--> 113 new_args = [conversion.py2rpy(a) for a in args]
114 new_kwargs = {}
115 for k, v in kwargs.items():
~/anaconda3/envs/catenv/lib/python3.7/functools.py in wrapper(*args, **kw)
838 '1 positional argument')
839
--> 840 return dispatch(args[0].__class__)(*args, **kw)
841
842 funcname = getattr(func, '__name__', 'singledispatch function')
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/robjects/pandas2ri.py in py2rpy_pandasdataframe(obj)
59 'The error is: %s'
60 % (name, str(e)))
---> 61 od[name] = StrVector(values)
62
63 return DataFrame(od)
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/robjects/vectors.py in __init__(self, obj)
382
383 def __init__(self, obj):
--> 384 super().__init__(obj)
385 self._add_rops()
386
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/rinterface_lib/sexp.py in __init__(self, obj)
286 super().__init__(obj)
287 elif isinstance(obj, collections.abc.Sized):
--> 288 super().__init__(type(self).from_object(obj).__sexp__)
289 else:
290 raise TypeError('The constructor must be called '
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/rinterface_lib/sexp.py in from_object(cls, obj)
370 except (TypeError, ValueError):
371 try:
--> 372 res = cls.from_iterable(obj)
373 except ValueError:
374 msg = ('The class methods from_memoryview() and '
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/rinterface_lib/conversion.py in _(*args, **kwargs)
26 def _cdata_res_to_rinterface(function):
27 def _(*args, **kwargs):
---> 28 cdata = function(*args, **kwargs)
29 # TODO: test cdata is of the expected CType
30 return _cdata_to_rinterface(cdata)
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/rinterface_lib/sexp.py in from_iterable(cls, iterable, populate_func)
317 if populate_func is None:
318 cls._populate_r_vector(iterable,
--> 319 r_vector)
320 else:
321 populate_func(iterable, r_vector)
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/rinterface_lib/sexp.py in _populate_r_vector(cls, iterable, r_vector)
300 r_vector,
301 cls._R_SET_VECTOR_ELT,
--> 302 cls._CAST_IN)
303
304 #classmethod
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/rinterface_lib/sexp.py in _populate_r_vector(iterable, r_vector, set_elt, cast_value)
237 def _populate_r_vector(iterable, r_vector, set_elt, cast_value):
238 for i, v in enumerate(iterable):
--> 239 set_elt(r_vector, i, cast_value(v))
240
241
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/rinterface_lib/sexp.py in _as_charsxp_cdata(x)
430 return x.__sexp__._cdata
431 else:
--> 432 return conversion._str_to_charsxp(x)
433
434
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/rinterface_lib/conversion.py in _str_to_charsxp(val)
118 s = rlib.R_NaString
119 else:
--> 120 cchar = _str_to_cchar(val)
121 s = rlib.Rf_mkCharCE(cchar, _CE_UTF8)
122 return s
~/anaconda3/envs/catenv/lib/python3.7/site-packages/rpy2/rinterface_lib/conversion.py in _str_to_cchar(s, encoding)
97 def _str_to_cchar(s, encoding: str = 'utf-8'):
98 # TODO: use isStrinb and installTrChar
---> 99 b = s.encode(encoding)
100 return ffi.new('char[]', b)
101
AttributeError: 'float' object has no attribute 'encode'
So I find that it is not possible to even start an R magic cell while importing my pandas dataframe object. However, I have tried creating R vectors inside the cell, and find I can plot these using ggplot2 with no issues.
I am using Python 3.7.6, rpy2 3.1.0, jupyter-notebook 6.0.3and am using Ubuntu 18.04.2 LTS on Windows Subsystem for Linux.

The problem is most likely with one (or more) columns having more than one type - therefore it is impossible to transfer the data into an R vector (which can hold only one data type). The traceback may be overwhelming, but here is the relevant part:
ValueError: Series can only be of one type, or None.
Which column it is? Difficult to say without looking at the dataset that you load, but my general solution is to check the types in the columns:
types = data.applymap(type).apply(set)
types[types.apply(len) > 1]
Anything returned by the snippet above would be a candidate culprit. There are many different ways of dealing with the problem, depending on the exact nature of the data. Workarounds that I frequently use include:
calling data = data.infer_objects() - helps if the pandas did not catch up with a dtype change and still stores the data with (suboptimal) Python objects
filling NaN with an empty string or a string constant if you have missing values in a string column (e.g. str_columns = str_columns.fillna(''))
dates.apply(pd.to_datetime, axis=1) if you have datetime objects but the dtype is object
using df.applymap(lambda x: datetime.combine(x, datetime.min.time()) if not isinstance(x, datetime) else x) if you have a mixture of date and datetime objects
In some vary rare cases pandas stores the data differently than expected by rpy2 (following certain manipulations); then writing the dataframe down to a csv file and reading it from the disk again helps - but this is likely not what you are facing here, as you start from a newly read dataframe.

I just noticed there might be an even simpler reason for the problem. For some reason, pandas2ri requires you to call pandas2ri.activate()after importing it. This solved the problem for me.

"Error while extracting" from tensorflow datasets

I want to train a tensorflow image segmentation model on COCO, and thought I would leverage the dataset builder already included. Download seems to be completed but it crashes on extracting the zip files.
Running with TF 2.0.0 on a Jupyter Notebook under a conda environment. Computer is 64-bit Windows 10. The Oxford Pet III dataset used in the official image segmentation tutorial works fine.
Below is the error message (my local user name replaced with %user%).
---------------------------------------------------------------------------
OutOfRangeError Traceback (most recent call last)
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\extractor.py in _sync_extract(self, from_path, method, to_path)
88 try:
---> 89 for path, handle in iter_archive(from_path, method):
90 path = tf.compat.as_text(path)
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\extractor.py in iter_zip(arch_f)
176 with _open_or_pass(arch_f) as fobj:
--> 177 z = zipfile.ZipFile(fobj)
178 for member in z.infolist():
~\.conda\envs\tf-tutorial\lib\zipfile.py in __init__(self, file, mode, compression, allowZip64)
1130 if mode == 'r':
-> 1131 self._RealGetContents()
1132 elif mode in ('w', 'x'):
~\.conda\envs\tf-tutorial\lib\zipfile.py in _RealGetContents(self)
1193 try:
-> 1194 endrec = _EndRecData(fp)
1195 except OSError:
~\.conda\envs\tf-tutorial\lib\zipfile.py in _EndRecData(fpin)
263 # Determine file size
--> 264 fpin.seek(0, 2)
265 filesize = fpin.tell()
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_core\python\util\deprecation.py in new_func(*args, **kwargs)
506 instructions)
--> 507 return func(*args, **kwargs)
508
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_core\python\lib\io\file_io.py in seek(self, offset, whence, position)
166 elif whence == 2:
--> 167 offset += self.size()
168 else:
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_core\python\lib\io\file_io.py in size(self)
101 """Returns the size of the file."""
--> 102 return stat(self.__name).length
103
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_core\python\lib\io\file_io.py in stat(filename)
726 """
--> 727 return stat_v2(filename)
728
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_core\python\lib\io\file_io.py in stat_v2(path)
743 file_statistics = pywrap_tensorflow.FileStatistics()
--> 744 pywrap_tensorflow.Stat(compat.as_bytes(path), file_statistics)
745 return file_statistics
OutOfRangeError: C:\Users\%user%\tensorflow_datasets\downloads\images.cocodataset.org_zips_train20147eQIfmQL3bpVDgkOrnAQklNLVUtCsFrDPwMAuYSzF3U.zip; Unknown error
During handling of the above exception, another exception occurred:
ExtractError Traceback (most recent call last)
<ipython-input-27-887fa0198611> in <module>
1 cocoBuilder = tfds.builder('coco')
2 info = cocoBuilder.info
----> 3 cocoBuilder.download_and_prepare()
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\api_utils.py in disallow_positional_args_dec(fn, instance, args, kwargs)
50 _check_no_positional(fn, args, ismethod, allowed=allowed)
51 _check_required(fn, kwargs)
---> 52 return fn(*args, **kwargs)
53
54 return disallow_positional_args_dec(wrapped) # pylint: disable=no-value-for-parameter
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\dataset_builder.py in download_and_prepare(self, download_dir, download_config)
285 self._download_and_prepare(
286 dl_manager=dl_manager,
--> 287 download_config=download_config)
288
289 # NOTE: If modifying the lines below to put additional information in
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\dataset_builder.py in _download_and_prepare(self, dl_manager, download_config)
946 super(GeneratorBasedBuilder, self)._download_and_prepare(
947 dl_manager=dl_manager,
--> 948 max_examples_per_split=download_config.max_examples_per_split,
949 )
950
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\dataset_builder.py in _download_and_prepare(self, dl_manager, **prepare_split_kwargs)
802 # Generating data for all splits
803 split_dict = splits_lib.SplitDict()
--> 804 for split_generator in self._split_generators(dl_manager):
805 if splits_lib.Split.ALL == split_generator.split_info.name:
806 raise ValueError(
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\image\coco.py in _split_generators(self, dl_manager)
237 root_url = 'http://images.cocodataset.org/'
238 extracted_paths = dl_manager.download_and_extract({
--> 239 key: root_url + url for key, url in urls.items()
240 })
241
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\download_manager.py in download_and_extract(self, url_or_urls)
357 with self._downloader.tqdm():
358 with self._extractor.tqdm():
--> 359 return _map_promise(self._download_extract, url_or_urls)
360
361 #property
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\download_manager.py in _map_promise(map_fn, all_inputs)
393 """Map the function into each element and resolve the promise."""
394 all_promises = utils.map_nested(map_fn, all_inputs) # Apply the function
--> 395 res = utils.map_nested(_wait_on_promise, all_promises)
396 return res
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\utils\py_utils.py in map_nested(function, data_struct, dict_only, map_tuple)
127 return {
128 k: map_nested(function, v, dict_only, map_tuple)
--> 129 for k, v in data_struct.items()
130 }
131 elif not dict_only:
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\utils\py_utils.py in <dictcomp>(.0)
127 return {
128 k: map_nested(function, v, dict_only, map_tuple)
--> 129 for k, v in data_struct.items()
130 }
131 elif not dict_only:
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\utils\py_utils.py in map_nested(function, data_struct, dict_only, map_tuple)
141 return tuple(mapped)
142 # Singleton
--> 143 return function(data_struct)
144
145
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\download_manager.py in _wait_on_promise(p)
377
378 def _wait_on_promise(p):
--> 379 return p.get()
380
381 else:
~\.conda\envs\tf-tutorial\lib\site-packages\promise\promise.py in get(self, timeout)
508 target = self._target()
509 self._wait(timeout or DEFAULT_TIMEOUT)
--> 510 return self._target_settled_value(_raise=True)
511
512 def _target_settled_value(self, _raise=False):
~\.conda\envs\tf-tutorial\lib\site-packages\promise\promise.py in _target_settled_value(self, _raise)
512 def _target_settled_value(self, _raise=False):
513 # type: (bool) -> Any
--> 514 return self._target()._settled_value(_raise)
515
516 _value = _reason = _target_settled_value
~\.conda\envs\tf-tutorial\lib\site-packages\promise\promise.py in _settled_value(self, _raise)
222 if _raise:
223 raise_val = self._fulfillment_handler0
--> 224 reraise(type(raise_val), raise_val, self._traceback)
225 return self._fulfillment_handler0
226
~\.conda\envs\tf-tutorial\lib\site-packages\six.py in reraise(tp, value, tb)
694 if value.__traceback__ is not tb:
695 raise value.with_traceback(tb)
--> 696 raise value
697 finally:
698 value = None
~\.conda\envs\tf-tutorial\lib\site-packages\promise\promise.py in handle_future_result(future)
840 # type: (Any) -> None
841 try:
--> 842 resolve(future.result())
843 except Exception as e:
844 tb = exc_info()[2]
~\.conda\envs\tf-tutorial\lib\concurrent\futures\_base.py in result(self, timeout)
423 raise CancelledError()
424 elif self._state == FINISHED:
--> 425 return self.__get_result()
426
427 self._condition.wait(timeout)
~\.conda\envs\tf-tutorial\lib\concurrent\futures\_base.py in __get_result(self)
382 def __get_result(self):
383 if self._exception:
--> 384 raise self._exception
385 else:
386 return self._result
~\.conda\envs\tf-tutorial\lib\concurrent\futures\thread.py in run(self)
54
55 try:
---> 56 result = self.fn(*self.args, **self.kwargs)
57 except BaseException as exc:
58 self.future.set_exception(exc)
~\.conda\envs\tf-tutorial\lib\site-packages\tensorflow_datasets\core\download\extractor.py in _sync_extract(self, from_path, method, to_path)
92 except BaseException as err:
93 msg = 'Error while extracting %s to %s : %s' % (from_path, to_path, err)
---> 94 raise ExtractError(msg)
95 # `tf.io.gfile.Rename(overwrite=True)` doesn't work for non empty
96 # directories, so delete destination first, if it already exists.
ExtractError: Error while extracting C:\Users\%user%\tensorflow_datasets\downloads\images.cocodataset.org_zips_train20147eQIfmQL3bpVDgkOrnAQklNLVUtCsFrDPwMAuYSzF3U.zip to C:\Users\%user%\tensorflow_datasets\downloads\extracted\ZIP.images.cocodataset.org_zips_train20147eQIfmQL3bpVDgkOrnAQklNLVUtCsFrDPwMAuYSzF3U.zip : C:\Users\%user%\tensorflow_datasets\downloads\images.cocodataset.org_zips_train20147eQIfmQL3bpVDgkOrnAQklNLVUtCsFrDPwMAuYSzF3U.zip; Unknown error
The message seems cryptic to me. The folder to which it is trying to extract does not exist when the notebook is started - it is created by Tensorflow, and only at that command line. I obviously tried deleting it completely and running it again, to no effect.
The code that leads to the error is (everything runs fine until the last line):
import tensorflow as tf
from __future__ import absolute_import, division, print_function, unicode_literals
from tensorflow_examples.models.pix2pix import pix2pix
import tensorflow_datasets as tfds
from IPython.display import clear_output
import matplotlib.pyplot as plt
dataset, info = tfds.load('coco', with_info=True)
Also tried breaking down the last command into assigning the tdfs.builder object and then running download_and_extract, and again got the same error.
There is enough space in disk - after download, still 50+GB available, while the dataset is supposed to be 37GB in its largest version (2014).

I have a similar problem with Windows 10 & COCO 2017. My solution is simple. Extract the ZIP file manually according to the folder path in the error message.

Version of raise is a syntax error in Python 3

As a rookie, I just started to use the datareader library, in particular read_html function and came across the following error when trying to get a table from websites.
import pandas as pd
from pandas_datareader import data
df_list=pd.read_html('https://www.mismarcadores.com/futbol/espana/laliga/clasificacion/')
print(len(df_list))
And I get this syntax error with raise (line 346)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-44-c546df3e8ebd> in <module>()
----> 1 df_list=pd.read_html('https://www.mismarcadores.com/futbol/espana/laliga/clasificacion/')
2 print(len(df_list))
~\Anaconda3\lib\site-packages\pandas\io\html.py in read_html(io, match, flavor, header, index_col, skiprows, attrs, parse_dates, tupleize_cols, thousands, encoding, decimal, converters, na_values, keep_default_na)
904 thousands=thousands, attrs=attrs, encoding=encoding,
905 decimal=decimal, converters=converters, na_values=na_values,
--> 906 keep_default_na=keep_default_na)
~\Anaconda3\lib\site-packages\pandas\io\html.py in _parse(flavor, io, match, attrs, encoding, **kwargs)
741 break
742 else:
--> 743 raise_with_traceback(retained)
744
745 ret = []
~\Anaconda3\lib\site-packages\pandas\compat\__init__.py in raise_with_traceback(exc, traceback)
342 if traceback == Ellipsis:
343 _, _, traceback = sys.exc_info()
--> 344 raise exc.with_traceback(traceback)
345 else:
346 # this version of raise is a syntax error in Python 3
ValueError: No tables found
Checking the HTML code there's actually a table tag on that url, and I do not understand why it does not pick it out...
Thanks a lot for your help.