(Assuming we don't want to disallow 1-level MultiIndexes), stop identifying MultiIndex by nlevels == 1

[toobaz]

Code Sample, a copy-pastable example if possible

In [2]: mi = pd.MultiIndex.from_product([[0, 1]])

In [3]: mi.set_names(('first',), level=0)
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-3-1f4ad6c7f0bf> in <module>()
----> 1 mi.set_names(('first',), level=0)

/home/nobackup/repo/pandas/pandas/core/indexes/base.py in set_names(self, names, level, inplace)
   1386 
   1387         if level is not None and self.nlevels == 1:
-> 1388             raise ValueError('Level must be None for non-MultiIndex')
   1389 
   1390         if level is not None and not is_list_like(level) and is_list_like(

ValueError: Level must be None for non-MultiIndex

Problem description

The case of MultiIndex with self.nlevels == 1 is currently perfectly valid (despite e.g. MultiIndex.droplevel returning a normal Index when only one level is left). Unless we want to change this, we should always identify a MultiIndex with isinstance, not by looking at self.nlevels.

Expected Output

In [4]: mi.set_names(('first',))
Out[4]: 
MultiIndex(levels=[[0, 1]],
           labels=[[0, 1]],
           names=['first'])

Output of pd.show_versions()

INSTALLED VERSIONS

commit: 5cf4957
python: 3.5.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.0-6-amd64
machine: x86_64
processor:
byteorder: little
LC_ALL: None
LANG: it_IT.UTF-8
LOCALE: it_IT.UTF-8

pandas: 0.24.0.dev0+14.g5cf4957a2.dirty
pytest: 3.5.0
pip: 9.0.1
setuptools: 39.0.1
Cython: 0.25.2
numpy: 1.14.3
scipy: 0.19.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: 1.5.6
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: 1.2.0dev
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: 1.3.0
xlsxwriter: 0.9.6
lxml: 4.1.1
bs4: 4.5.3
html5lib: 0.999999999
sqlalchemy: 1.0.15
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.2.1

[toobaz]

Another way to see it is: a 1-level MultiIndex and a flat index should behave the same way 99% of time (there can be exceptions), and hence the test which is raising a ValueError above has no reason to be there.

[jreback]

yes this would be nice to fix

[KalyanGokhale]

@toobaz can I submit the suggested fix? unless you were planning to incorporate in another PR...

[toobaz]

@toobaz can I submit the suggested fix? unless you were planning to incorporate in another PR...

You're welcome to go on... but there are in total three checks of self.nlevels == 1 or self.nlevels > 1 in the same file, it could be great if you could take care of all of them together (or verify they don't need any change).

[KalyanGokhale]

Sure - of two self.nlevels statement in def set_names, at one place change is needed and at the other its not needed - and I have made the fix.

For one self.nlevels statement in def cmp_method in the same file pandas/core/indexes/base.py, I am evaluating a few test cases - and will submit a single PR once done.