a b bar foo A0 D 0 2 3 1 A1 D 16 18 19 17 A2 D 32 34 35 33 A3 D 48 50 51 49 A4 D 64 66 67 65 --------------------------------------------------------------------------- TypeError Traceback (most recent call last) /opt/conda/lib/python3.8/site-packages/pandas/core/arrays/categorical.py in __init__(self, values, categories, ordered, dtype, fastpath) 342 try: --> 343 codes, categories = factorize(values, sort=True) 344 except TypeError as err: /opt/conda/lib/python3.8/site-packages/pandas/core/algorithms.py in factorize(values, sort, na_sentinel, size_hint) 676 --> 677 codes, uniques = _factorize_array( 678 values, na_sentinel=na_sentinel, size_hint=size_hint, na_value=na_value /opt/conda/lib/python3.8/site-packages/pandas/core/algorithms.py in _factorize_array(values, na_sentinel, size_hint, na_value, mask) 499 table = hash_klass(size_hint or len(values)) --> 500 uniques, codes = table.factorize( 501 values, na_sentinel=na_sentinel, na_value=na_value, mask=mask pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.factorize() pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable._unique() TypeError: unhashable type: 'slice' During handling of the above exception, another exception occurred: TypeError Traceback (most recent call last) /opt/conda/lib/python3.8/site-packages/pandas/core/indexes/multi.py in get_indexer(self, target, method, limit, tolerance) 2443 try: -> 2444 target = MultiIndex.from_tuples(target) 2445 except (TypeError, ValueError): /opt/conda/lib/python3.8/site-packages/pandas/core/indexes/multi.py in from_tuples(cls, tuples, sortorder, names) 506 --> 507 return MultiIndex.from_arrays(arrays, sortorder=sortorder, names=names) 508 /opt/conda/lib/python3.8/site-packages/pandas/core/indexes/multi.py in from_arrays(cls, arrays, sortorder, names) 438 --> 439 codes, levels = factorize_from_iterables(arrays) 440 if names is lib.no_default: /opt/conda/lib/python3.8/site-packages/pandas/core/arrays/categorical.py in factorize_from_iterables(iterables) 2724 return [[], []] -> 2725 return map(list, zip(*(factorize_from_iterable(it) for it in iterables))) /opt/conda/lib/python3.8/site-packages/pandas/core/arrays/categorical.py in (.0) 2724 return [[], []] -> 2725 return map(list, zip(*(factorize_from_iterable(it) for it in iterables))) /opt/conda/lib/python3.8/site-packages/pandas/core/arrays/categorical.py in factorize_from_iterable(values) 2696 # from ordered. Set ordered to False as default. See GH #15457 -> 2697 cat = Categorical(values, ordered=False) 2698 categories = cat.categories /opt/conda/lib/python3.8/site-packages/pandas/core/arrays/categorical.py in __init__(self, values, categories, ordered, dtype, fastpath) 344 except TypeError as err: --> 345 codes, categories = factorize(values, sort=False) 346 if dtype.ordered: /opt/conda/lib/python3.8/site-packages/pandas/core/algorithms.py in factorize(values, sort, na_sentinel, size_hint) 676 --> 677 codes, uniques = _factorize_array( 678 values, na_sentinel=na_sentinel, size_hint=size_hint, na_value=na_value /opt/conda/lib/python3.8/site-packages/pandas/core/algorithms.py in _factorize_array(values, na_sentinel, size_hint, na_value, mask) 499 table = hash_klass(size_hint or len(values)) --> 500 uniques, codes = table.factorize( 501 values, na_sentinel=na_sentinel, na_value=na_value, mask=mask pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.factorize() pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable._unique() TypeError: unhashable type: 'slice' During handling of the above exception, another exception occurred: TypeError Traceback (most recent call last) /opt/conda/lib/python3.8/site-packages/IPython/core/formatters.py in __call__(self, obj) 343 method = get_real_method(obj, self.print_method) 344 if method is not None: --> 345 return method() 346 return None 347 else: /opt/conda/lib/python3.8/site-packages/pandas/io/formats/style.py in _repr_html_(self) 191 Hooks into Jupyter notebook rich display system. 192 """ --> 193 return self.render() 194 195 @doc(NDFrame.to_excel, klass="Styler") /opt/conda/lib/python3.8/site-packages/pandas/io/formats/style.py in render(self, **kwargs) 538 * table_attributes 539 """ --> 540 self._compute() 541 # TODO: namespace all the pandas keys 542 d = self._translate() /opt/conda/lib/python3.8/site-packages/pandas/io/formats/style.py in _compute(self) 623 r = self 624 for func, args, kwargs in self._todo: --> 625 r = func(self)(*args, **kwargs) 626 return r 627 /opt/conda/lib/python3.8/site-packages/pandas/io/formats/style.py in _apply(self, func, axis, subset, **kwargs) 635 subset = slice(None) if subset is None else subset 636 subset = _non_reducing_slice(subset) --> 637 data = self.data.loc[subset] 638 if axis is not None: 639 result = data.apply(func, axis=axis, result_type="expand", **kwargs) /opt/conda/lib/python3.8/site-packages/pandas/core/indexing.py in __getitem__(self, key) 871 # AttributeError for IntervalTree get_value 872 pass --> 873 return self._getitem_tuple(key) 874 else: 875 # we by definition only have the 0th axis /opt/conda/lib/python3.8/site-packages/pandas/core/indexing.py in _getitem_tuple(self, tup) 1042 def _getitem_tuple(self, tup: Tuple): 1043 try: -> 1044 return self._getitem_lowerdim(tup) 1045 except IndexingError: 1046 pass /opt/conda/lib/python3.8/site-packages/pandas/core/indexing.py in _getitem_lowerdim(self, tup) 764 # we may have a nested tuples indexer here 765 if self._is_nested_tuple_indexer(tup): --> 766 return self._getitem_nested_tuple(tup) 767 768 # we maybe be using a tuple to represent multiple dimensions here /opt/conda/lib/python3.8/site-packages/pandas/core/indexing.py in _getitem_nested_tuple(self, tup) 845 846 current_ndim = obj.ndim --> 847 obj = getattr(obj, self.name)._getitem_axis(key, axis=axis) 848 axis += 1 849 /opt/conda/lib/python3.8/site-packages/pandas/core/indexing.py in _getitem_axis(self, key, axis) 1097 raise ValueError("Cannot index with multidimensional key") 1098 -> 1099 return self._getitem_iterable(key, axis=axis) 1100 1101 # nested tuple slicing /opt/conda/lib/python3.8/site-packages/pandas/core/indexing.py in _getitem_iterable(self, key, axis) 1035 1036 # A collection of keys -> 1037 keyarr, indexer = self._get_listlike_indexer(key, axis, raise_missing=False) 1038 return self.obj._reindex_with_indexers( 1039 {axis: [keyarr, indexer]}, copy=True, allow_dups=True /opt/conda/lib/python3.8/site-packages/pandas/core/indexing.py in _get_listlike_indexer(self, key, axis, raise_missing) 1247 1248 if ax.is_unique and not getattr(ax, "is_overlapping", False): -> 1249 indexer = ax.get_indexer_for(keyarr) 1250 keyarr = ax.reindex(keyarr)[0] 1251 else: /opt/conda/lib/python3.8/site-packages/pandas/core/indexes/base.py in get_indexer_for(self, target, **kwargs) 4711 """ 4712 if self.is_unique: -> 4713 return self.get_indexer(target, **kwargs) 4714 indexer, _ = self.get_indexer_non_unique(target, **kwargs) 4715 return indexer /opt/conda/lib/python3.8/site-packages/pandas/core/indexes/multi.py in get_indexer(self, target, method, limit, tolerance) 2447 # let's instead try with a straight Index 2448 if method is None: -> 2449 return Index(self._values).get_indexer( 2450 target, method=method, limit=limit, tolerance=tolerance 2451 ) /opt/conda/lib/python3.8/site-packages/pandas/core/indexes/base.py in get_indexer(self, target, method, limit, tolerance) 3004 ) 3005 -> 3006 indexer = self._engine.get_indexer(target._get_engine_target()) 3007 3008 return ensure_platform_int(indexer) pandas/_libs/index.pyx in pandas._libs.index.IndexEngine.get_indexer() pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.PyObjectHashTable.lookup() TypeError: unhashable type: 'slice'