wide_to_long ignores columns which start with something else than a digit
#### Code Sample, a copy-pastable example if possible

```python
df = pd.DataFrame({"A X1970" : {0 : "a", 1 : "b", 2 : "c"},
                    "A X1980" : {0 : "d", 1 : "e", 2 : "f"},
                    "B X1970" : {0 : 2.5, 1 : 1.2, 2 : .7},
                    "B X1980" : {0 : 3.2, 1 : 1.3, 2 : .1},
                    "X"     : dict(zip(range(3), np.random.randn(3)))
                   })
df["id"] = df.index
pd.wide_to_long(df, ["A", "B"], i="id", j="xyear", sep=' ')

```
#### Problem description

wide_to_long gets confused when the stub is not a string representation of a number. 
If you delete X's from the example above everything will work fine. 
With the X's however it stops working and the returned dataframe has zero rows.

#### Expected Output

dataframe with more than zero rows

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

<details>

INSTALLED VERSIONS
------------------
commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Linux
OS-release: 4.4.0-64-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: None
pip: 9.0.1
setuptools: 35.0.2
Cython: None
numpy: 1.13.1
scipy: 0.19.1
xarray: None
IPython: 6.1.0
sphinx: None
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.2
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.0.2
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: None
html5lib: 0.999999999
sqlalchemy: 1.1.11
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: 0.1.2
pandas_gbq: None
pandas_datareader: None

</details>
