DataFrame.fillna() downcast argument does not work when the value for fillna is a dict instead of a scalar

[albertvillanova]

Code Sample, a copy-pastable example if possible

import pandas as pd

df = pd.DataFrame({'a': [1, None]})

df1 = df.fillna(0, downcast='infer')
df2 = df.fillna({'a': 0}, downcast='infer')

print(df1)
print(df2)

Problem description

When using the method DataFrame.fillna(), the downcast option is not working when the value for fillna is a dict instead of a scalar.

Expected Output

In both previous DataFrame examples, the column should be downcasted to integer dtype instead of float.

Output of pd.show_versions()

commit: None python: 3.5.2.final.0 python-bits: 64 OS: Linux OS-release: 3.13.0-107-generic machine: x86_64 processor: x86_64 byteorder: little LC_ALL: None LANG: ca_ES.UTF-8

pandas: 0.18.1
nose: 1.3.7
pip: 8.1.2
setuptools: 27.2.0.post20161106
Cython: 0.24.1
numpy: 1.11.1
scipy: 0.18.1
statsmodels: 0.6.1
xarray: None
IPython: 5.1.0
sphinx: 1.4.6
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.6.1
blosc: None
bottleneck: 1.1.0
tables: 3.2.3.1
numexpr: 2.6.1
matplotlib: 1.5.3
openpyxl: 2.3.2
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.3
lxml: 3.6.4
bs4: 4.5.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.13
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.42.0
pandas_datareader: 0.2.1