Description
Code Sample, a copy-pastable example if possible
df = pd.DataFrame({'col1': [0, 1, 2, 3], 'col2': ['a', 'b', None, 'd'], 'col3': ['e', 'f', None, 'h']})
df.min(axis=0, skipna=True)
Problem description
If I've read the documentation correctly I think min should return a series of the same length as the relevant axis of the dataframe, and especially with the skipna flag set as True (which is the default) NA values should be ignored in the calculation.
Output
col1 0
dtype: int64
Expected Output
col1 0
col2 a
col3 e
dtype: object
Output of pd.show_versions()
INSTALLED VERSIONS
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Windows
OS-release: 10
machine: AMD64
processor: Intel64 Family 6 Model 78 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
pandas: 0.20.3
pytest: 3.0.7
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.12.1
scipy: 0.19.0
xarray: None
IPython: 5.3.0
sphinx: 1.5.6
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.2.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.7
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.3
bs4: 4.6.0
html5lib: 0.999
sqlalchemy: 1.1.9
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None