COMPAT: df.to_dict('index') is not preserving dtypes
#### Code Sample

```python
import pandas as pd
from pandas.core.common import standardize_mapping

df = pd.DataFrame(dict(ints=range(5),floats=[float(i) for i in range(5)]))

into_c = standardize_mapping(dict)

print('Using iterrows:')
print(into_c((k, v.to_dict(dict)) for k, v in df.iterrows()))

```
#### Problem description

The problem appears when trying to export dataframe to dict using 'index' as param and when that dataframe conatains both float and int. Expected behaviour would be to separate ints and floats (as shown below). iAs recommended by the docs, we could use itertuples instead. I have included a code-snippet that could work. (Disclaimer: Sorry, this might be a pull request but I thought it could fit here since I'm not feeling familiar with the whole process)

#### Expected Output

```python
{0: {'ints': 0, 'floats': 0.0}, 1: {'ints': 1, 'floats': 1.0}, 2: {'ints': 2, 'floats': 2.0}, 3: {'ints': 3, 'floats': 3.0}, 4: {'ints': 4, 'floats': 4.0}}

print('\nUsing itertuples:')
print(into_c((t[0],dict(zip(df.columns,t[1:]))) for t in df.itertuples()))

```

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Darwin
OS-release: 14.5.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: en_US.UTF-8
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.21.0
pytest: 2.9.2
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.24.1
numpy: 1.13.1
scipy: 0.18.1
pyarrow: None
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
feather: None
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
sqlalchemy: 1.0.13
pymysql: None
psycopg2: None
jinja2: 2.8
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
