DOC: update the pandas.core.generic.NDFrame.to_clipboard docstring
Checklist for the pandas documentation sprint (ignore this if you are doing
an unrelated PR):

- [X] PR title is "DOC: update the <your-function-or-method> docstring"
- [X] The validation script passes: `scripts/validate_docstrings.py pandas.core.generic.NDFrame.to_clipboard`
- [X] The PEP8 style check passes: `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [X] The html version looks good: `python doc/make.py --single pandas.core.generic.NDFrame.to_clipboard`
- [X] It has been proofread on language by another sprint participant

Please include the output of the validation script below between the "```" ticks:

```
################################################################################
############# Docstring (pandas.core.generic.NDFrame.to_clipboard) #############
################################################################################

Copy object to the system clipboard.

Write a text representation of object to the system clipboard.
This can be pasted into Excel, for example.

Parameters
----------
excel : bool
    Default setting for this argument is True.
    If True, use the provided separator, writing in a csv format for
    allowing easy pasting into excel.
    If False, write a string representation of the object to the
    clipboard.
sep : str, default tab
    Field delimiter.
kwargs : optional
    These parameters will be passed to either
    :py:meth:`pandas.DataFrame.to_csv`
    or :py:meth:`pandas.Series.to_csv` methods depending on the
    Object type.

See Also
--------
pandas.core.frame.DataFrame.to_csv : Write a DataFrame to a
    comma-separated values (csv) file.
pandas.core.series.Series.to_csv : Write a Series to a
    comma-separated values (csv) file.

Notes
-----
Requirements for your platform.
  - Linux : `xclip`, or `xsel` (with `gtk` or `PyQt4` modules)
  - Windows : none
  - OS X : none

Examples
--------
Copy the contents of a DataFrame to the clipboard.

>>> df = pd.DataFrame([[1, 2, 3], [4, 5, 6]], columns=['A', 'B', 'C'])
>>> df.to_clipboard()

We can omit the the index by passing the keyword 'index' and setting it to false.

>>> df.to_clipboard(index=False)

################################################################################
################################## Validation ##################################
################################################################################
```

If the validation script still gives errors, but you think there is a good reason
to deviate in this case (and there are certainly such cases), please state this
explicitly.