DOC: update the pandas.Index.drop_duplicates and pandas.Series.drop_duplicates docstring
State: closed

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>`
- [ ] 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.drop_duplicates```:

```
################################################################################
################### Docstring (pandas.Index.drop_duplicates) ###################
################################################################################

Return Index with duplicate values removed.

The drop_duplicates method can remove occurences or whole sets
of duplicated entries in a pandas.Index object.

Parameters
----------
keep : {'first', 'last', ``False``}, default 'first'
    - 'first' : Drop duplicates except for the first occurrence.
    - 'last' : Drop duplicates except for the last occurrence.
    - ``False`` : Drop all duplicates.

Returns
-------
deduplicated : Index

See Also
--------
pandas.Series.drop_duplicates : equivalent method on pandas.Series

Examples
--------
Generate an pandas.Index with duplicate values.

>>> idx = pd.Index(['lama', 'cow', 'lama', 'beetle', 'lama', 'hippo'])

With the 'keep' parameter, the selection behaviour of duplicated values
can be changed. The value 'first' keeps the first occurrence for each
set of duplicated entries. The default value of keep is 'first'.

>>> idx.drop_duplicates(keep='first')
Index(['lama', 'cow', 'beetle', 'hippo'], dtype='object')

The value 'last' keeps the last occurrence for each set of duplicated
entries.

>>> idx.drop_duplicates(keep='last')
Index(['cow', 'beetle', 'lama', 'hippo'], dtype='object')

The value ``False`` discards all sets of duplicated entries.

>>> idx.drop_duplicates(keep=False)
Index(['cow', 'beetle', 'hippo'], dtype='object')

################################################################################
################################## Validation ##################################
################################################################################

Errors found:
	Errors in parameters section
		Parameter "keep" description should start with capital letter

```

Method ```pandas.Series.drop_duplicates```:

```

################################################################################
################## Docstring (pandas.Series.drop_duplicates)  ##################
################################################################################

Return Series with duplicate values removed.

The drop_duplicates method can remove occurences or whole sets
of duplicated entries in a pandas.Series object.

Parameters
----------
keep : {'first', 'last', ``False``}, default 'first'
    - 'first' : Drop duplicates except for the first occurrence.
    - 'last' : Drop duplicates except for the last occurrence.
    - ``False`` : Drop all duplicates.
inplace : boolean, default ``False``
    If ``True``, performs operation inplace and returns None.

Returns
-------
deduplicated : Series

See Also
--------
pandas.Index.drop_duplicates : equivalent method on pandas.Index

Examples
--------
Generate an Series with duplicated entries.

>>> s = pd.Series(['lama', 'cow', 'lama', 'beetle', 'lama', 'hippo'],
...               name='animal')
>>> s
0      lama
1       cow
2      lama
3    beetle
4      lama
5     hippo
Name: animal, dtype: object

With the 'keep' parameter, the selection behaviour of duplicated values
can be changed. The value 'first' keeps the first occurrence for each
set of duplicated entries. The default value of keep is 'first'.

>>> s.drop_duplicates()
0      lama
1       cow
3    beetle
5     hippo
Name: animal, dtype: object

The value 'last' for parameter 'keep' keeps the last occurrence for
each set of duplicated entries.

>>> s.drop_duplicates(keep='last')
1       cow
3    beetle
4      lama
5     hippo
Name: animal, dtype: object

The value ``False`` for parameter 'keep' discards all sets of
duplicated entries. Setting the value of 'inplace' to ``True`` performs
the operation inplace and returns ``None``.

>>> s.drop_duplicates(keep=False, inplace=True)
>>> s
1       cow
3    beetle
5     hippo
Name: animal, dtype: object

################################################################################
################################## 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.

The parameter keyword fails in the validation script. In the DOC sprint team, it was decided that summing up the parameter values is more valuable.

Labels:
name: Docs

Comments:
Well, we were having this discussion here as well :-) 
I said them to start with making both, and then we could afterwards see what they would really have in common. In this case it is mainly the Parameters section. So we could also have a variables with this text, and inject only that part in both docstrings. Not sure if that will be simpler though