Indexing MultiIndex level depends on chosen level #12827
Description
Code Sample, a copy-pastable example if possible
In [2]: ss = pd.Series(range(4), ...: index=pd.MultiIndex.from_product([[1,2], [1,2]])) In [3]: ss.loc[:, 1].index.__class__ Out[3]: pandas.indexes.numeric.Int64Index In [4]: ss.loc[1,:].index.__class__ Out[4]: pandas.indexes.multi.MultiIndex Expected Output
The first: the level I am indexing on should disappear from the index.
This is related to http://stackoverflow.com/q/36459311/2858145 (I think)
output of pd.show_versions()
In [5]: pd.show_versions() INSTALLED VERSIONS ------------------ commit: None python: 2.7.10.final.0 python-bits: 64 OS: Linux OS-release: 4.4.0-1-amd64 machine: x86_64 processor: byteorder: little LC_ALL: None LANG: it_IT.utf8 pandas: 0.18.0+88.g5e11243.dirty nose: 1.3.6 pip: 1.5.6 setuptools: 18.4 Cython: 0.23.2 numpy: 1.10.4 scipy: 0.16.0 statsmodels: 0.8.0.dev0+755fa81 xarray: None IPython: 2.4.1 sphinx: 1.3.1 patsy: 0.3.0-dev dateutil: 2.2 pytz: 2012c blosc: None bottleneck: None tables: 3.2.2 numexpr: 2.4.3 matplotlib: 1.5.0rc2 openpyxl: 2.3.0 xlrd: 0.9.4 xlwt: 0.7.5 xlsxwriter: 0.7.3 lxml: 3.4.4 bs4: 4.4.0 html5lib: 0.999 httplib2: 0.9.1 apiclient: None sqlalchemy: 1.0.11 pymysql: None psycopg2: 2.6.1 (dt dec mx pq3 ext lo64) jinja2: 2.8 boto: 2.38.0 pandas_datareader: None