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

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@toobaz

Description

@toobaz

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

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    BugDtype ConversionsUnexpected or buggy dtype conversionsIndexRelated to the Index class or subclassesNeeds TestsUnit test(s) needed to prevent regressions

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