DOC: update the DataFrame.plot.line 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"
- [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:

```❯ python scripts/validate_docstrings.py pandas.DataFrame.plot.line

################################################################################
#################### Docstring (pandas.DataFrame.plot.line) ####################
################################################################################

Plot DataFrame columns as lines.

This function is useful to plot lines using DataFrame's values
as coordinates.

Parameters
----------
x : int or str, optional
    Columns to use for the horizontal axis.
    Either the location or the label of the columns to be used.
    By default, it will use the `DataFrame` indices.
y : int, str, or list of them, optional
    The values to be plotted.
    Either the location or the label of the columns to be used.
    By default, it will use the remaining DataFrame numeric columns.
kwds : optional
    Keyword arguments to pass on to :py:meth:pandas.DataFrame.plot.

Returns
-------
axes : :class:matplotlib.AxesSubplot or :class:numpy.ndarray of
       them.

See Also
--------
matplotlib.pyplot.plot : Plot y versus x as lines and/or markers.

Examples
--------

.. plot::
    :context: close-figs

    The following example shows the populations for some animals
    over the years.

    >>> df = pd.DataFrame({
    ...    'pig': [20, 18, 489, 675, 1776],
    ...    'horse': [4, 25, 281, 600, 1900]
    ...    }, index=[1990, 1997, 2003, 2009, 2014])
    >>> lines = df.plot.line()

.. plot::
    :context: close-figs

    The following example shows the relationship between both
    populations.

    >>> lines = df.plot.line(x='pig', y='horse')

################################################################################
################################## Validation ##################################
################################################################################

Docstring for "pandas.DataFrame.plot.line" 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.




Labels:
name: Docs
name: Visualization
description: plotting

Comments:
Fixes are up now
# [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/20163?src=pr&el=h1) Report
> :exclamation: No coverage uploaded for pull request base (`master@f85ae92`). [Click here to learn what that means](https://docs.codecov.io/docs/error-reference#section-missing-base-commit).
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/pandas-dev/pandas/pull/20163/graphs/tree.svg?src=pr&width=650&height=150&token=eZ4WkYLtcO)](https://codecov.io/gh/pandas-dev/pandas/pull/20163?src=pr&el=tree)

```diff
@@            Coverage Diff            @@
##             master   #20163   +/-   ##
=========================================
  Coverage          ?   91.72%           
=========================================
  Files             ?      150           
  Lines             ?    49152           
  Branches          ?        0           
=========================================
  Hits              ?    45086           
  Misses            ?     4066           
  Partials          ?        0
```

| Flag | Coverage Δ | |
|---|---|---|
| #multiple | `90.11% <ø> (?)` | |
| #single | `41.84% <ø> (?)` | |

| [Impacted Files](https://codecov.io/gh/pandas-dev/pandas/pull/20163?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [pandas/plotting/\_core.py](https://codecov.io/gh/pandas-dev/pandas/pull/20163/diff?src=pr&el=tree#diff-cGFuZGFzL3Bsb3R0aW5nL19jb3JlLnB5) | `82.23% <ø> (ø)` | |

------

[Continue to review full report at Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/20163?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/20163?src=pr&el=footer). Last update [f85ae92...75b1a22](https://codecov.io/gh/pandas-dev/pandas/pull/20163?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).

Thanks @TomAugspurger !
Thank you!