read_csv with filehandler and nrows argument
#### Code Sample, a copy-pastable example if possible



```python
%%file example.csv
1,2
3,4
5,6
7,8
9,10
11,12
```




```python
import pandas as pd
```


```python
with open('example.csv') as f:
    data = pd.read_csv(f, names=['A', 'B'], nrows=2)
    print(f.readline())
```

```
```



```python
with open('example.csv') as f:
    data = pd.read_csv(f, names=['A', 'B'], nrows=1, engine='python')
    print(f.readline())
    print(f.readline())
    print(data)
```

    7,8
    
    9,10
    
       A  B
    0  1  2



```python
with open('example.csv') as f:
    data = pd.read_csv(f, names=['A', 'B'], nrows=2, engine='python')
    print(f.readline())
    print(f.readline())
    print(data)
```

    7,8
    
    9,10
    
       A  B
    0  1  2
    1  3  4



```python
with open('example.csv') as f:
    data = pd.read_csv(f, names=['A', 'B'], nrows=3, engine='python')
    print(f.readline())
    print(f.readline())
    print(data)
```

    7,8
    
    9,10
    
       A  B
    0  1  2
    1  3  4
    2  5  6



#### Problem description

The Issue https://github.com/pandas-dev/pandas/issues/2071 is probably related.
The c-parser exhaustes the file handler even if nrows is passed.

The python-parser shows unexpected behaviour, when ``nrows=1`` or ``nrows=2`` is given. 


#### Expected Output

```python
with open('example.csv') as f:
    data = pd.read_csv(f, names=['A', 'B'], nrows=2, engine='python')
    print(f.readline())
    print(f.readline())
    print(data)
```

    5,6
    
    7,8
    
       A  B
    0  1  2
    1  3  4



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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.6.2.final.0
python-bits: 64
OS: Linux
OS-release: 4.10.0-27-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.20.3
pytest: 3.1.2
pip: 9.0.1
setuptools: 27.2.0
Cython: 0.25.2
numpy: 1.13.1
scipy: 0.19.1
xarray: None
IPython: 6.1.0
sphinx: 1.6.2
patsy: 0.4.1
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: 1.2.1
tables: 3.3.0
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: 2.4.0-b1
xlrd: 1.0.0
xlwt: 1.2.0
xlsxwriter: 0.9.6
lxml: 3.8.0
bs4: 4.6.0
html5lib: 0.999
sqlalchemy: 1.1.11
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None
</details>
