Closed
Description
Code Sample, a copy-pastable example if possible
In [2]: df = pd.DataFrame([[1, 2]], columns=pd.MultiIndex.from_product([['A'], ['a', 'b']]))
In [3]: reind = df.set_index([('A', 'a')])
In [4]: reind.reset_index()
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
/home/pietro/nobackup/repo/pandas/pandas/util/hashing.py in hash_array(vals, encoding, hash_key, categorize)
265 try:
--> 266 vals = _hash.hash_object_array(vals, hash_key, encoding)
267 except TypeError:
as/pandas/util/hashing.pyx in pandas.util.libhashing.hash_object_array (pandas/util/hashing.c:2372)()
TypeError: ('A', 'a') of type <class 'tuple'> is not a valid type for hashing, must be string or null
During handling of the above exception, another exception occurred:
ValueError Traceback (most recent call last)
<ipython-input-4-985862d3b27d> in <module>()
----> 1 reind.reset_index()
/home/pietro/nobackup/repo/pandas/pandas/core/frame.py in reset_index(self, level, drop, inplace, col_level, col_fill)
3057 name = tuple(name_lst)
3058 values = _maybe_casted_values(self.index)
-> 3059 new_obj.insert(0, name, values)
3060
3061 new_obj.index = new_index
/home/pietro/nobackup/repo/pandas/pandas/core/frame.py in insert(self, loc, column, value, allow_duplicates)
2518 value = self._sanitize_column(column, value, broadcast=False)
2519 self._data.insert(loc, column, value,
-> 2520 allow_duplicates=allow_duplicates)
2521
2522 def assign(self, **kwargs):
/home/pietro/nobackup/repo/pandas/pandas/core/internals.py in insert(self, loc, item, value, allow_duplicates)
3806
3807 """
-> 3808 if not allow_duplicates and item in self.items:
3809 # Should this be a different kind of error??
3810 raise ValueError('cannot insert {}, already exists'.format(item))
/home/pietro/nobackup/repo/pandas/pandas/core/indexes/multi.py in __contains__(self, key)
1326 hash(key)
1327 try:
-> 1328 self.get_loc(key)
1329 return True
1330 except LookupError:
/home/pietro/nobackup/repo/pandas/pandas/core/indexes/multi.py in get_loc(self, key, method)
1984 key = _values_from_object(key)
1985 key = tuple(map(_maybe_str_to_time_stamp, key, self.levels))
-> 1986 return self._engine.get_loc(key)
1987
1988 # -- partial selection or non-unique index
/home/pietro/nobackup/repo/pandas/pandas/_libs/index.pyx in pandas._libs.index.MultiIndexEngine.get_loc (pandas/_libs/index.c:13171)()
/home/pietro/nobackup/repo/pandas/pandas/_libs/index.pyx in pandas._libs.index.MultiIndexEngine.get_loc (pandas/_libs/index.c:13018)()
/home/pietro/nobackup/repo/pandas/pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.MultiIndexHashTable.get_item (pandas/_libs/hashtable.c:23625)()
/home/pietro/nobackup/repo/pandas/pandas/_libs/hashtable_class_helper.pxi in pandas._libs.hashtable.MultiIndexHashTable.get_item (pandas/_libs/hashtable.c:23374)()
/home/pietro/nobackup/repo/pandas/pandas/core/indexes/multi.py in _hashed_indexing_key(self, key)
755 key = tuple([f(k, stringify)
756 for k, stringify in zip(key, self._have_mixed_levels)])
--> 757 return hash_tuples(key)
758
759 @Appender(base._shared_docs['duplicated'] % _index_doc_kwargs)
/home/pietro/nobackup/repo/pandas/pandas/util/hashing.py in hash_tuples(vals, encoding, hash_key)
159 hash_key=hash_key)
160 for cat in vals)
--> 161 h = _combine_hash_arrays(hashes, len(vals))
162 if is_tuple:
163 h = h[0]
/home/pietro/nobackup/repo/pandas/pandas/util/hashing.py in _combine_hash_arrays(arrays, num_items)
31 """
32 try:
---> 33 first = next(arrays)
34 except StopIteration:
35 return np.array([], dtype=np.uint64)
/home/pietro/nobackup/repo/pandas/pandas/util/hashing.py in <genexpr>(.0)
158 encoding=encoding,
159 hash_key=hash_key)
--> 160 for cat in vals)
161 h = _combine_hash_arrays(hashes, len(vals))
162 if is_tuple:
/home/pietro/nobackup/repo/pandas/pandas/util/hashing.py in _hash_categorical(c, encoding, hash_key)
182 """
183 hashed = hash_array(c.categories.values, encoding, hash_key,
--> 184 categorize=False)
185
186 # we have uint64, as we don't directly support missing values
/home/pietro/nobackup/repo/pandas/pandas/util/hashing.py in hash_array(vals, encoding, hash_key, categorize)
267 except TypeError:
268 # we have mixed types
--> 269 vals = _hash.hash_object_array(vals.astype(str).astype(object),
270 hash_key, encoding)
271
ValueError: setting an array element with a sequenceProblem description
In general, one expects df.set_index([df.columns[0]]).reset_index() to return (a copy of) df. Instead, this does not happen if df.columns is a MultiIndex.
@jreback I know you were not really convinced this should work, but I'm uploading a PR in a couple of minutes, and as you will see the fix is extremely simple.
Expected Output
df
Output of pd.show_versions()
INSTALLED VERSIONS
commit: None
python: 3.5.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.7.0-1-amd64
machine: x86_64
processor:
byteorder: little
LC_ALL: None
LANG: it_IT.utf8
LOCALE: it_IT.UTF-8
pandas: 0.20.0rc1+29.g075eca1fa
pytest: 3.0.6
pip: 9.0.1
setuptools: 33.1.1
Cython: 0.25.2
numpy: 1.12.0
scipy: 0.18.1
xarray: 0.9.1
IPython: 5.1.0.dev
sphinx: 1.4.9
patsy: 0.3.0-dev
dateutil: 2.5.3
pytz: 2016.7
blosc: None
bottleneck: 1.2.0
tables: 3.3.0
numexpr: 2.6.1
feather: 0.3.1
matplotlib: 2.0.0
openpyxl: 2.3.0
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.6
lxml: 3.7.1
bs4: 4.5.3
html5lib: 0.999999999
sqlalchemy: 1.0.15
pymysql: None
psycopg2: None
jinja2: 2.8
s3fs: None
pandas_gbq: None
pandas_datareader: 0.2.1