Kernel dies when using df.to_hdf
#### Code Sample

```python

import os
import sys
import tempfile

import pandas as pd
from urllib.request import urlretrieve

# Settings
p_ext = 'https://ftp.ncbi.nlm.nih.gov/gene/DATA/gene_info.gz'
p_down = os.path.join(tempfile.gettempdir(), 'tmp_gene_info.gz')
p_out = os.path.join(tempfile.gettempdir(), 'tmp_gene_info.h5')

# Notify about usage of version of python and pandas, where error occurred
if sys.version.startswith('3.6.0 '):
    print('You are using the same python version, where the problem occurred.')

if pd.__version__ == '0.19.2':
    print('You are using the same pandas version, where the problem occurred.')

# Download dataset where error occurred
urlretrieve(p_ext, p_down)

# Get dataframe
df = pd.read_table(p_down, sep='\t', header=0)
df = df.drop_duplicates(['#tax_id', 'GeneID'])

# Attempt to save as Hdf5
# A process where kernel would die, approx. 2 seconds after memory usage
# approaches the limit of my machine (62GB out of 64GB)
df.to_hdf(
    p_out,
    'table',
    mode='w',
    append=True,
    data_columns=['#tax_id', 'GeneID'])

```
#### Problem description

Kernel dies while exporting DataFrame to HDF5. This death occurs on two different machines of mine. The error occurs both, in iPython notebooks, and when running the script through command line.

I have not been facing problems with df.to_hdf on any other (and smaller) DataFrames (or subsets of the given DataFrame), which suggests that there might be some problem with the specific data set. 

Prior to the death of the kernel, RAM usage shoots up to around 62GB of 64GB. Thus I am not sure, if my issue relates to some bug, or whether it would be a request for the implementation of a low-memory fall-back.


#### Expected Output

The DataFrame would become saved as an HDF5 file.

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

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.0.final.0
python-bits: 64
OS: Darwin
OS-release: 16.4.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.19.2
nose: 1.3.7
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.11.3
scipy: 0.18.1
statsmodels: 0.6.1
xarray: None
IPython: 5.1.0
sphinx: 1.5.1
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2016.10
blosc: None
bottleneck: 1.2.0
tables: 3.3.0
numexpr: 2.6.1
matplotlib: 2.0.0
openpyxl: 2.4.1
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.7.2
bs4: 4.5.3
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.1.5
pymysql: None
psycopg2: None
jinja2: 2.9.4
boto: 2.45.0
pandas_datareader: None
</details>
