Skip to content

Initializing a Series from and Index discards the "dtype" argument #17088

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Closed
toobaz opened this issue Jul 26, 2017 · 3 comments · Fixed by #27107
Closed

Initializing a Series from and Index discards the "dtype" argument #17088

toobaz opened this issue Jul 26, 2017 · 3 comments · Fixed by #27107
Labels
Bug Dtype Conversions Unexpected or buggy dtype conversions Index Related to the Index class or subclasses Needs Tests Unit test(s) needed to prevent regressions

Comments

@toobaz
Copy link
Member

toobaz commented Jul 26, 2017

Code Sample, a copy-pastable example if possible

In [2]: pd.Series(pd.Index([1,2,3]), dtype='bool').dtype
Out[2]: dtype('int64')

In [3]: pd.Series(pd.Index([1,2,3]), dtype='int32').dtype
Out[3]: dtype('int64')

In [4]: pd.Series(pd.Index([1,2,3]), dtype='float64').dtype
Out[4]: dtype('int64')

Problem description

The dtype should be enforced when explicitly passed; instead the dtype of the original index is preserved. Compare to:

n [5]: pd.Series(pd.Index([1,2,3]).astype('bool'), dtype='bool').dtype
Out[5]: dtype('O')

In [6]: pd.Series(pd.Index([1,2,3]).astype('float64'), dtype='float64').dtype
Out[6]: dtype('float64')

Expected Output

Initialization with index should behave analogously to initialization from a list or numpy array:

In [7]: pd.Series([1,2,3], dtype='bool').dtype
Out[7]: dtype('bool')

In [8]: pd.Series([1,2,3], dtype='float64').dtype
Out[8]: dtype('float64')

Output of pd.show_versions()

INSTALLED VERSIONS ------------------ commit: 395f712 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: 0.21.0.dev+301.g395f71213
pytest: 3.0.6
pip: 9.0.1
setuptools: None
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
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: 2.0.2
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
pandas_gbq: None
pandas_datareader: 0.2.1
pyarrow: None

@gfyoung gfyoung added Dtype Conversions Unexpected or buggy dtype conversions Indexing Related to indexing on series/frames, not to indexes themselves Bug labels Jul 26, 2017
@gfyoung
Copy link
Member

gfyoung commented Jul 26, 2017

Yeah...that's not right (I wouldn't see why / how that's intended behavior). PR to patch is welcome!

@jreback
Copy link
Contributor

jreback commented Jul 26, 2017

hmm, we coerce when dtype is passed, but maybe this fails. [2] should raise. I think there is a PR out there (maybe closed, but not merged), which is re-factoring this to handle correctly, if you'd have a look.

@toobaz toobaz added Index Related to the Index class or subclasses and removed Indexing Related to indexing on series/frames, not to indexes themselves labels Jun 28, 2019
@toobaz
Copy link
Member Author

toobaz commented Jun 28, 2019

The behavior was fixed at some time, adding a test

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
Bug Dtype Conversions Unexpected or buggy dtype conversions Index Related to the Index class or subclasses Needs Tests Unit test(s) needed to prevent regressions
Projects
None yet
Development

Successfully merging a pull request may close this issue.

3 participants