BUG: to_clipboard() incorrectly claims I have specified a non-single character separator in excel mode.
### 

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.

- [x] I have confirmed this bug exists on the master branch of pandas.


### Reproducible Example

```python
import pandas as pd
df = pd.DataFrame({'numbers': [1, 2, 3], 'colors': ['red', 'white', 'blue']})
df.to_clipboard(index_names=False, header=False)
```

Gives the following trace. 

```python-trace
C:\ProgramData\Miniforge3\lib\site-packages\pandas\io\clipboards.py:133: UserWarning: to_clipboard in excel mode requires a single character separator.
  warnings.warn(
```



### Issue Description

The same error occurs regardless of whether I do not specify a separator, or if I include sep="," as an argument. In both cases, I am not specifying a separator of more than 1 character and there should be no problem passing this to to_csv().  

Inspecting the source code at https://github.com/pandas-dev/pandas/blob/master/pandas/io/clipboards.py it appears we are correctly being caught by the `if excel` statement on line 120 (since we are in excel mode by default) but the try/except wrapper around the call to to_csv() is catching a TypeError. Further inspection is needed to identify what is causing the exception. 

Tested in both pandas v1.2.3 and latest version v1.3.4. 
I'm using miniconda on Windows 10. 

### Expected Behavior

The dataframe should be copied to the clipboard as string text without an exception being caught. 

### Installed Versions

<details>

INSTALLED VERSIONS
------------------
commit           : 945c9ed766a61c7d2c0a7cbb251b6edebf9cb7d5
python           : 3.8.12.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
Version          : 10.0.18363
machine          : AMD64
processor        : Intel64 Family 6 Model 142 Stepping 12, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : en

pandas           : 1.3.4
numpy            : 1.21.2
pytz             : 2021.3
dateutil         : 2.8.2
pip              : 21.3
setuptools       : 58.2.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : 4.2.0
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.6.3
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 3.0.2
IPython          : 7.28.0
pandas_datareader: None
bs4              : 4.10.0
bottleneck       : None
fsspec           : 2021.10.1
fastparquet      : None
gcsfs            : None
matplotlib       : 3.4.3
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.7.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
