Read_csv leaks memory when used in multiple threads
When using `read_csv` in threads it appears that the Python process leaks a little memory.

This is coming from this dask-focused stack overflow question: https://stackoverflow.com/questions/48954080/why-is-dask-read-csv-from-s3-keeping-so-much-memory

I've reduced it to a problem with `pandas.read_csv` and a `concurrent.futures.ThreadPoolExecutor`

#### Code Sample, a copy-pastable example if possible

```python
# imports
import pandas as pd
import numpy as np
import time
import psutil
from concurrent.futures import ThreadPoolExecutor

# prep
process = psutil.Process()
e = ThreadPoolExecutor(8)
```

```python
# prepare csv file, only need to run once
pd.DataFrame(np.random.random((100000, 50))).to_csv('large_random.csv')
```

```python
# baseline computation making pandas dataframes with threasds.  This works fine

def f(_):
    return pd.DataFrame(np.random.random((1000000, 50)))

print('before:', process.memory_info().rss // 1e6, 'MB')
list(e.map(f, range(8)))
time.sleep(1)  # let things settle
print('after:', process.memory_info().rss // 1e6, 'MB')
```
```
before: 57.0 MB
after: 56.0 MB
```

```python
# example with read_csv, this leaks memory
print('before:', process.memory_info().rss // 1e6, 'MB')
list(e.map(pd.read_csv, ['large_random.csv'] * 8))
time.sleep(1)  # let things settle
print('after:', process.memory_info().rss // 1e6, 'MB')
```

```
before: 58.0 MB
after: 323.0 MB
```

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

<details>
In [2]: pd.show_versions()

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.2.final.0
python-bits: 64
OS: Linux
OS-release: 4.13.0-26-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.22.0
pytest: 3.3.2
pip: 9.0.1
setuptools: 38.4.0
Cython: 0.28a0
numpy: 1.14.1
scipy: 0.19.0
pyarrow: 0.8.0
xarray: 0.8.2-264-g0b2424a
IPython: 5.1.0
sphinx: 1.6.5
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.3
blosc: 1.5.1
bottleneck: None
tables: 3.3.0
numexpr: 2.6.2
feather: None
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
sqlalchemy: 1.2.1
pymysql: None
psycopg2: 2.7.1 (dt dec pq3 ext lo64)
jinja2: 2.10
s3fs: 0.0.9
fastparquet: 0.1.4
pandas_gbq: None
pandas_datareader: None

</details>
