DOC: update the pandas.Series.map 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 <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:

```
################################################################################
######################## Docstring (pandas.Series.map)  ########################
################################################################################

Map values of Series according to input correspondence.

Used for substituting each value in a Series with another value,
that may be derived from a function, a ``dict`` or
a :class:`pandas.Series`.

Parameters
----------
arg : function, dict, or Seriess
    Mapping correspondence.
na_action : {None, 'ignore'}
    If 'ignore', propagate NA values, without passing them to the
    mapping correspondence.

Returns
-------
y : Series
    Same index as caller.

Examples
--------

Map inputs to outputs (both of type :class:`pandas.Series`):

>>> x = pd.Series([1,2,3], index=['one', 'two', 'three'])
>>> x
one      1
two      2
three    3
dtype: int64

>>> y = pd.Series(['foo', 'bar', 'baz'], index=[1,2,3])
>>> y
1    foo
2    bar
3    baz
dtype: object

>>> x.map(y)
one   foo
two   bar
three baz
dtype: object

Map a function to a :class:`pandas.Series`.

>>> x.map(lambda x: x**2)
one      1
two      4
three    9
dtype: int64

If ``arg`` is a dictionary, return a new :class:`pandas.Series` with
values converted according to the dictionary's mapping:

>>> z = {1: 'A', 2: 'B', 3: 'C'}

>>> x.map(z)
one   A
two   B
three C
dtype: object

Use ``na_action`` to control whether NA values are affected by the
mapping function.

>>> s = pd.Series([1, 2, 3, np.nan])

>>> s.map('this is a string {}'.format, na_action=None)
0    this is a string 1.0
1    this is a string 2.0
2    this is a string 3.0
3    this is a string nan
dtype: object

>>> s.map('this is a string {}'.format, na_action='ignore')
0    this is a string 1.0
1    this is a string 2.0
2    this is a string 3.0
3                     NaN
dtype: object

See Also
--------
Series.apply : For applying more complex functions on a Series.
DataFrame.apply : Apply a function row-/column-wise.
DataFrame.applymap : Apply a function elementwise on a whole DataFrame.

Notes
-----
When `arg` is a dictionary, values in Series that are not in the
dictionary (as keys) are converted to ``NaN``. However, if the
dictionary is a ``dict`` subclass that defines ``__missing__`` (i.e.
provides a method for default values), then this default is used
rather than ``NaN``:

>>> from collections import Counter
>>> counter = Counter()
>>> counter['bar'] += 1
>>> y.map(counter)
1    0
2    1
3    0
dtype: int64

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

Docstring for "pandas.Series.map" correct. :)
```

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.


Checklist for other PRs (remove this part if you are doing a PR for the pandas documentation sprint):

- [ ] closes #xxxx
- [ ] tests added / passed
- [ ] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [ ] whatsnew entry

# [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/20450?src=pr&el=h1) Report
> Merging [#20450](https://codecov.io/gh/pandas-dev/pandas/pull/20450?src=pr&el=desc) into [master](https://codecov.io/gh/pandas-dev/pandas/commit/92dcf5f4cce9c7221c8556f0251ec56095cc1b2b?src=pr&el=desc) will **decrease** coverage by `0.27%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/pandas-dev/pandas/pull/20450/graphs/tree.svg?width=650&height=150&token=eZ4WkYLtcO&src=pr)](https://codecov.io/gh/pandas-dev/pandas/pull/20450?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master   #20450      +/-   ##
==========================================
- Coverage   92.05%   91.77%   -0.28%     
==========================================
  Files         169      152      -17     
  Lines       50713    49216    -1497     
==========================================
- Hits        46683    45170    -1513     
- Misses       4030     4046      +16
```

| Flag | Coverage Δ | |
|---|---|---|
| #multiple | `90.16% <ø> (-0.3%)` | :arrow_down: |
| #single | `41.84% <ø> (-0.41%)` | :arrow_down: |

| [Impacted Files](https://codecov.io/gh/pandas-dev/pandas/pull/20450?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [pandas/core/series.py](https://codecov.io/gh/pandas-dev/pandas/pull/20450/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvc2VyaWVzLnB5) | `93.84% <ø> (+0.11%)` | :arrow_up: |
| [pandas/io/s3.py](https://codecov.io/gh/pandas-dev/pandas/pull/20450/diff?src=pr&el=tree#diff-cGFuZGFzL2lvL3MzLnB5) | `72.72% <0%> (-13.64%)` | :arrow_down: |
| [pandas/util/\_doctools.py](https://codecov.io/gh/pandas-dev/pandas/pull/20450/diff?src=pr&el=tree#diff-cGFuZGFzL3V0aWwvX2RvY3Rvb2xzLnB5) | `0% <0%> (-12.88%)` | :arrow_down: |
| [pandas/core/reshape/util.py](https://codecov.io/gh/pandas-dev/pandas/pull/20450/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvcmVzaGFwZS91dGlsLnB5) | `90.32% <0%> (-9.68%)` | :arrow_down: |
| [pandas/util/\_decorators.py](https://codecov.io/gh/pandas-dev/pandas/pull/20450/diff?src=pr&el=tree#diff-cGFuZGFzL3V0aWwvX2RlY29yYXRvcnMucHk=) | `82.4% <0%> (-8.95%)` | :arrow_down: |
| [pandas/core/arrays/base.py](https://codecov.io/gh/pandas-dev/pandas/pull/20450/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvYXJyYXlzL2Jhc2UucHk=) | `80.64% <0%> (-7.22%)` | :arrow_down: |
| [pandas/core/common.py](https://codecov.io/gh/pandas-dev/pandas/pull/20450/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvY29tbW9uLnB5) | `92.04% <0%> (-5.3%)` | :arrow_down: |
| [pandas/io/formats/terminal.py](https://codecov.io/gh/pandas-dev/pandas/pull/20450/diff?src=pr&el=tree#diff-cGFuZGFzL2lvL2Zvcm1hdHMvdGVybWluYWwucHk=) | `16.43% <0%> (-4.82%)` | :arrow_down: |
| [pandas/io/formats/printing.py](https://codecov.io/gh/pandas-dev/pandas/pull/20450/diff?src=pr&el=tree#diff-cGFuZGFzL2lvL2Zvcm1hdHMvcHJpbnRpbmcucHk=) | `89.38% <0%> (-3.71%)` | :arrow_down: |
| [pandas/core/dtypes/missing.py](https://codecov.io/gh/pandas-dev/pandas/pull/20450/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvZHR5cGVzL21pc3NpbmcucHk=) | `91.07% <0%> (-1.92%)` | :arrow_down: |
| ... and [104 more](https://codecov.io/gh/pandas-dev/pandas/pull/20450/diff?src=pr&el=tree-more) | |

------

[Continue to review full report at Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/20450?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/20450?src=pr&el=footer). Last update [92dcf5f...fae8f19](https://codecov.io/gh/pandas-dev/pandas/pull/20450?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
 @kaoboyandy will you have time to update based on @datapythonista's comments? Thanks @kaoboyandy and @datapythonista !