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stack() casts to float when called on levels not requiring it #17886
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xref #17845 |
again a special case where you have a cartesian product |
For future reference (I'll try to produce PRs for this and #17845 when I find the time): this can actually be catched without actually looking at index values, because every time we stack all levels but one we obviously don't introduce any missing value. |
Other reminder: when this is fixed, remove workaround in tests. |
@toobaz hopefully fixing this issue will break that test (until work-around is removed)! |
Well, no, the workaround should just then cast from int... to int, but it should still work. |
With |
Code Sample, a copy-pastable example if possible
Problem description
Casting to float is not required (notice it would have been if
df.stack()
had been called without arguments).Expected Output
Output of
pd.show_versions()
INSTALLED VERSIONS
commit: 6793a136dde139d968948b6ec9193cc3535abf6f
python: 3.5.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.0-3-amd64
machine: x86_64
processor:
byteorder: little
LC_ALL: None
LANG: it_IT.UTF-8
LOCALE: it_IT.UTF-8
pandas: 0.21.0rc1+13.g6793a136d.dirty
pytest: 3.0.6
pip: 9.0.1
setuptools: None
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
pyarrow: None
xarray: None
IPython: 5.1.0.dev
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.3.0
numexpr: 2.6.1
feather: 0.3.1
matplotlib: 2.0.0
openpyxl: None
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.6
lxml: None
bs4: 4.5.3
html5lib: 0.999999999
sqlalchemy: 1.0.15
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.2.1
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