Dataframe loading with duplicated columns and usecols
I'm using pandas 0.17.1

``` python
import pandas as pd
  pd.__version__
```

`Out:'0.17.1'`

When column names are duplicated 

``` python
cols = ['A', 'A', 'B']
with open('pandas.csv', 'w') as f:
  f.write('1,2,3')
```

we can still load dataframe

``` python
pd.read_csv('pandas.csv',
            header=None,
            names=cols,
           )
```

 with explainable behaviour

```
Out:
     A    A    B
0    2    2    3
```

Then we might want to load some of the columns with python engine

``` python
pd.read_csv('pandas.csv',
            engine='python',
            header=None,
            names=cols,
            usecols=cols
           )
```

and get different but still explainable result

```
Out:
     A    B
0    1    3
```

But then we switch back to c-engine

``` python
pd.read_csv('pandas.csv',
            engine='c',
            header=None,
            names=cols,
            usecols=cols
           )
```

and get the following

```
Out:
     A    A    B
0    2    2    NaN
```

which is:
(a) different (which is not good in my opinion)
(b) looks like bug
