Code Sample, a copy-pastable example if possible
In [2]: s = pd.Series(dtype='object')
In [3]: s.loc['myint'] = 1
In [4]: s.loc['myfloat'] = 2.
In [5]: s
Out[5]:
myint 1.0
myfloat 2.0
dtype: float64
Problem description
When an empty Series is added the first object, it does inference on it and sets its dtype ( https://github.com/pandas-dev/pandas/issues/19576#issuecomment-363875752 ). This can be nice... except if the user had passed a specific dtype on construction.
Empty objects should (by default) have no dtype set (or have an "Any" dtype), and inference should be done only in this case.
Expected Output
Output of pd.show_versions()
INSTALLED VERSIONS
------------------
commit: None
python: 3.5.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.0-5-amd64
machine: x86_64
processor:
byteorder: little
LC_ALL: None
LANG: it_IT.UTF-8
LOCALE: it_IT.UTF-8
pandas: 0.19.2
nose: 1.3.7
pip: 9.0.1
setuptools: 33.1.1
Cython: 0.25.2
numpy: 1.13.3
scipy: 0.18.1
statsmodels: None
xarray: None
IPython: 5.1.0
sphinx: 1.4.9
patsy: 0.4.1+dev
dateutil: 2.5.3
pytz: 2016.7
blosc: None
bottleneck: 1.2.0
tables: 3.3.0
numexpr: 2.6.1
matplotlib: 2.0.0
openpyxl: 2.3.0
xlrd: 1.0.0
xlwt: None
xlsxwriter: 0.9.6
lxml: 3.7.1
bs4: 4.5.3
html5lib: 0.999999999
httplib2: 0.9.2
apiclient: None
sqlalchemy: 1.0.15
pymysql: None
psycopg2: None
jinja2: 2.8
boto: None
pandas_datareader: None