DOC: Update the pandas.Index.isna docstring
State: closed

Checklist for the pandas documentation sprint (ignore this if you are doing
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- [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>`
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```
################################################################################
######################## Docstring (pandas.Index.isna)  ########################
################################################################################

Detect missing values.

Return a boolean same-sized object indicating if the values are NA.
NA values, such as None or :attr:`numpy.NaN`, get mapped to True
values.
Everything else get mapped to False values. Characters such as empty
strings `''` or :attr:`numpy.inf` are not considered NA values
(unless you set :attr:`pandas.options.mode.use_inf_as_na` `= True`).

.. versionadded:: 0.20.0

Returns
-------
numpy.ndarray
    A boolean array of whether my values are NA

See also
--------
pandas.Index.isnull : alias of isna
pandas.Index.notna : boolean inverse of isna
pandas.Index.dropna : omit entries with missing values
pandas.isna : top-level isna

Examples
--------
Show which entries in a pandas.Index are NA. The result is a
array.

>>> idx = pd.Index([5.2, 6.0, np.NaN])
>>> idx
Float64Index([5.2, 6.0, nan], dtype='float64')
>>> idx.isna()
array([False, False,  True])

Empty strings are not considered NA values. None is considered a NA
value.

>>> idx = pd.Index(['black', '', 'red', None])
>>> idx
Index(['black', '', 'red', None], dtype='object')
>>> idx.isna()
array([False, False, False,  True])

################################################################################
################################## Validation ##################################
################################################################################

Docstring for "pandas.Index.isna" correct. :)
```



Labels:
name: Docs
name: Missing-data
description: np.nan, pd.NaT, pd.NA, dropna, isnull, interpolate

Comments:
Just a couple minor grammar things, otherwise this LGTM.
# [Codecov](https://codecov.io/gh/pandas-dev/pandas/pull/20123?src=pr&el=h1) Report
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```diff
@@            Coverage Diff            @@
##             master   #20123   +/-   ##
=========================================
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=========================================
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| Flag | Coverage Δ | |
|---|---|---|
| #multiple | `90.08% <ø> (?)` | |
| #single | `41.84% <ø> (?)` | |

| [Impacted Files](https://codecov.io/gh/pandas-dev/pandas/pull/20123?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [pandas/core/indexes/base.py](https://codecov.io/gh/pandas-dev/pandas/pull/20123/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvaW5kZXhlcy9iYXNlLnB5) | `96.66% <ø> (ø)` | |

------

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Thanks @donK23!