bug using `read_excel` and `index_col` option
### Code Sample, a copy-pastable example if possible

**Example 1 (weird column/value assignment)**
```
import pandas as pd

# Writing excel file with no column name in first column
tab = pd.DataFrame([['a', 'x'], ['b', 'y']], columns=['col1', 'col2'])
print('Original:\n', tab)
tab.to_excel('tmp_can_del.xlsx')

# The table read using read_excel assigns values of col1 to col2
new_tab = pd.read_excel('tmp_can_del.xlsx', index_col=2)
print('Read:\n', new_tab)
```

**Example 2 (index_col=None seems not to work)**
```
import pandas as pd

# Writing excel file with no column name in first column
tab = pd.DataFrame([['a', 'x'], ['b', 'y']], columns=['col1', 'col2'], index=['i1', 'i2'])
print('Original:\n', tab)
tab.to_excel('tmp_can_del.xlsx')

# The table read using read_excel should have three columns (`Unnamed: 0`, `col1`, `col2`) but just has two
new_tab = pd.read_excel('tmp_can_del.xlsx', index_col=None)
print('Read:\n', new_tab)
print(new_tab.columns)
```

### Problem description

The `index_col` option in `pd.read_excel` seems not to behave properly when the first column name is missing (for example, when a file is written using `to_excel(..., index=True)`).

**Example 1**
We end up with a DataFrame where the data for `col2` was originally the data below `col1`. This does not seem intuitive.

```
Original:
   col1 col2
0    a    x
1    b    y
Read:
    col1 col2
x     0    a
y     1    b
```

**Example 2**
It seems like the `index_col=None` option does not work. The first column  of the file is treated as the DataFrame index.

```
Original:
    col1 col2
i1    a    x
i2    b    y
Read:
    col1 col2
i1    a    x
i2    b    y
Index(['col1', 'col2'], dtype='object')
```
### Expected Output

**Example 1**
If column names are not specified, I would expect the data assigned to `col1` to be that below `col1` in the original excel file (same for `col2`).  Something like this:

```
Read:
    col1 col2
x     a    x
y     b    y
```

**Example 2**
I would expect the newly read tab to look somewhat like this (as is the case when doing the same operations using `write_csv` and `read_csv`):

```
   Unnamed: 0 col1 col2
0           i1    a    x
1           i2    b    y
```

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

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Linux
OS-release: 4.8.0-58-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: fr_FR.UTF-8
LOCALE: fr_FR.UTF-8

pandas: 0.21.1
pytest: 3.1.2
pip: 9.0.1
setuptools: 37.0.0
Cython: 0.25.2
numpy: 1.13.3
scipy: 0.19.1
pyarrow: None
xarray: None
IPython: 6.1.0
sphinx: 1.6.3
patsy: None
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: None
tables: None
numexpr: 2.6.2
feather: None
matplotlib: 2.0.2
openpyxl: None
xlrd: 1.0.0
xlwt: 1.3.0
xlsxwriter: 0.7.3
lxml: None
bs4: None
html5lib: 0.999999999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None

</details>
