DOC: update the pandas.Index.duplicated and pandas.Series.duplicated 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"
- [ ] The validation script passes: `scripts/validate_docstrings.py <your-function-or-method>`
- [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 <your-function-or-method>`
- [x] It has been proofread on language by another sprint participant

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

Method `pandas.Index.duplicated`:
```
################################################################################
##################### Docstring (pandas.Index.duplicated)  #####################
################################################################################

Indicate duplicate index values.

Duplicated values are indicated as ``True`` values in the resulting
array. Either all duplicates, all except the first or all except the
last occurrence of duplicates can be indicated.

Parameters
----------
keep : {'first', 'last', False}, default 'first'
    - 'first' : Mark duplicates as ``True`` except for the first
      occurrence.
    - 'last' : Mark duplicates as ``True`` except for the last
      occurrence.
    - ``False`` : Mark all duplicates as ``True``.

Examples
--------
By default, for each set of duplicated values, the first occurrence is
set on False and all others on True:

>>> idx = pd.Index(['lama', 'cow', 'lama', 'beetle', 'lama'])
>>> idx.duplicated()
array([False, False,  True, False,  True], dtype=bool)

which is equivalent to

>>> idx.duplicated(keep='first')
array([False, False,  True, False,  True], dtype=bool)

By using 'last', the last occurrence of each set of duplicated values
is set on False and all others on True:

>>> idx.duplicated(keep='last')
array([ True, False,  True, False, False], dtype=bool)

By setting keep on ``False``, all duplicates are True:

>>> idx.duplicated(keep=False)
array([ True, False,  True, False,  True], dtype=bool)

Returns
-------
numpy.ndarray

See Also
--------
pandas.Series.duplicated : equivalent method on pandas.Series

################################################################################
################################## Validation ##################################
################################################################################

Errors found:
	Errors in parameters section
		Parameter "keep" description should start with capital letter
```

Method `pandas.Series.duplicated`:
```
################################################################################
##################### Docstring (pandas.Series.duplicated) #####################
################################################################################

Indicate duplicate Series values.

Duplicated values are indicated as ``True`` values in the resulting
Series. Either all duplicates, all except the first or all except the
last occurrence of duplicates can be indicated.

Parameters
----------
keep : {'first', 'last', False}, default 'first'
    - 'first' : Mark duplicates as ``True`` except for the first
      occurrence.
    - 'last' : Mark duplicates as ``True`` except for the last
      occurrence.
    - ``False`` : Mark all duplicates as ``True``.

Examples
--------
By default, for each set of duplicated values, the first occurrence is
set on False and all others on True:

>>> animals = pd.Series(['lama', 'cow', 'lama', 'beetle', 'lama'])
>>> animals.duplicated()
0    False
1    False
2     True
3    False
4     True
dtype: bool

which is equivalent to

>>> animals.duplicated(keep='first')
0    False
1    False
2     True
3    False
4     True
dtype: bool

By using 'last', the last occurrence of each set of duplicated values
is set on False and all others on True:

>>> animals.duplicated(keep='last')
0     True
1    False
2     True
3    False
4    False
dtype: bool

By setting keep on ``False``, all duplicates are True:

>>> animals.duplicated(keep=False)
0     True
1    False
2     True
3    False
4     True
dtype: bool

Returnsinde
-------
pandas.core.series.Series

See Also
--------
pandas.Index.duplicated : equivalent method on pandas.Index

################################################################################
################################## Validation ##################################
################################################################################

Errors found:
	Errors in parameters section
		Parameter "keep" description should start with capital letter
```

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.

- We (Ghent chapter) decided that an additional line of text (with capital) was less useful than starting with explaining the list of options.

Instead of using the template-based version used before, we split out both docstrings and made a separate for the `Index` versus the `Series`. This introduces some redundancy and overlap (basically, the `keep` argument, also shared with `drop_duplicated`), but provides a cleaner option by having the examples written inside the docstring of the methods and not *somewhere* else in the code.