read_csv() is 3.5X Slower in Pandas 0.23.4 on Python 3.7.1 vs Pandas 0.22.0 on Python 3.5.2
#### Code Sample, a copy-pastable example if possible

```python
import io
import pandas as pd
import numpy as np
df = pd.DataFrame(np.random.randn(1000000, 10), columns=('COL{}'.format(i) for i in range(10)))
csv = io.StringIO(df.to_csv(index=False))
df2 = pd.read_csv(csv)

```
#### Problem description
``pd.read_csv()`` using ``_libs.parsers.TextReader``  ``read()`` method is 3.5X slower on Pandas 0.23.4 on Python 3.7.1 compared to Pandas 0.22.0 on Python 3.5.2.

```
 4244 function calls (4210 primitive calls) in 10.273 seconds

   Ordered by: internal time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1   10.202   10.202   10.204   10.204 {method 'read' of 'pandas._libs.parsers.TextReader' objects}
        1    0.039    0.039    0.039    0.039 internals.py:5017(_stack_arrays)
        1    0.011    0.011   10.262   10.262 parsers.py:414(_read)
        1    0.011    0.011   10.273   10.273 <string>:1(<module>)
        1    0.004    0.004    0.004    0.004 parsers.py:1685(__init__)
      321    0.001    0.000    0.002    0.000 common.py:811(is_integer_dtype)
```


#### Expected Output

```
3229 function calls (3222 primitive calls) in 2.944 seconds

   Ordered by: internal time

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    2.881    2.881    2.882    2.882 {method 'read' of 'pandas._libs.parsers.TextReader' objects}
        1    0.045    0.045    0.045    0.045 internals.py:4801(_stack_arrays)
        1    0.010    0.010    2.944    2.944 parsers.py:423(_read)
        1    0.004    0.004    0.004    0.004 parsers.py:1677(__init__)
      320    0.001    0.000    0.001    0.000 common.py:777(is_integer_dtype)
        1    0.001    0.001    0.001    0.001 {method 'close' of 'pandas._libs.p
```


#### Output of ``pd.show_versions() -- Latst Python 3.7.1 Pandas 0.23.4 : Slow Read CSV``


<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.7.1.final.0
python-bits: 64
OS: Windows
OS-release: 2008ServerR2
machine: AMD64
processor: Intel64 Family 6 Model 63 Stepping 2, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.23.4
pytest: 3.9.2
pip: 18.1
setuptools: 40.4.3
Cython: 0.29
numpy: 1.15.3
scipy: 1.1.0
pyarrow: 0.11.0
xarray: 0.10.9
IPython: 7.0.1
sphinx: 1.8.1
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.5
blosc: 1.6.1
bottleneck: 1.2.1
tables: 3.4.4
numexpr: 2.6.8
feather: None
matplotlib: 3.0.0
openpyxl: 2.5.9
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: None
lxml: 4.2.5
bs4: 4.6.3
html5lib: 1.0.1
sqlalchemy: 1.2.12
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: 0.1.6
pandas_gbq: None
pandas_datareader: None

</details>

#### Output of ``pd.show_versions() -- Older Python 3.5.2 Pandas 0.22.0 : Fast Read CSV``

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 63 Stepping 2, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None

pandas: 0.22.0
pytest: 3.5.0
pip: 9.0.3
setuptools: 20.10.1
Cython: 0.28.1
numpy: 1.14.2
scipy: 1.0.1
pyarrow: 0.9.0
xarray: 0.10.2
IPython: 6.3.0
sphinx: 1.7.2
patsy: 0.5.0
dateutil: 2.7.2
pytz: 2018.3
blosc: None
bottleneck: 1.2.1
tables: 3.4.2
numexpr: 2.6.4
feather: 0.4.0
matplotlib: 2.2.2
openpyxl: 2.5.1
xlrd: 1.1.0
xlwt: 1.3.0
xlsxwriter: None
lxml: 4.2.1
bs4: 4.6.0
html5lib: 0.9999999
sqlalchemy: 1.2.6
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: 0.1.5
pandas_gbq: None
pandas_datareader: None

</details>