DOC: update the pandas.DataFrame.to_sparse docstring
State: closed

Updates the docstring for the to_sparse function.

Here is the output of the validation script:
```

################################################################################
#################### Docstring (pandas.DataFrame.to_sparse) ####################
################################################################################

Convert to SparseDataFrame.

Implement the sparse version of the DataFrame meaning that any data matching
a specific value it's omitted in the representation. The sparse DataFrame takes
less memory on disk when pickled and in the Python interpreter.

Parameters
----------
fill_value : float, default NaN
    The specific value that should be omitted in the representation.
kind : {'block', 'integer'}
    The kind of the SparseIndex tracking where data has been omitted.
    The block kind is recommended since it’s more memory efficient:
    it tracks just the locations and sizes of the blocks of data that
    are not equal to the fill value while the integer kind keeps an
    array with all those locations.

Returns
-------
y : SparseDataFrame

See Also
--------
pandas.DataFrame.to_dense: converts the DataFrame back to the its dense form

Examples
--------

Compressing on the zero value.

>>> df = pd.DataFrame(np.random.randn(1000, 4))
>>> df.iloc[:995] = 0.
>>> sdf = df.to_sparse(fill_value=0.)
>>> sdf.density
0.005

################################################################################
################################## Validation ##################################
################################################################################

Docstring for "pandas.DataFrame.to_sparse" correct. :)
```


Labels:
name: Docs
name: Sparse
description: Sparse Data Type

Comments:
Hello @gioiab! Thanks for updating the PR.



Cheers ! There are no PEP8 issues in this Pull Request. :beers: 

##### Comment last updated on July 10, 2018 at 03:48 Hours UTC
@jreback I've implemented the changes you requested, I'm just waiting the CI to finish. Can you get a final look?
@jreback the Appveyor build failed, together with at least 50 other ones, all with the same error message: `Command executed with exception: Cannot index into a null array.`

I don't have a retry button to queue another build. Could you please help me on this? Thanks!
@jreback can I help you in some way in closing this? :)
@gioiab can you rebase

@datapythonista if you'd have a look
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| Flag | Coverage Δ | |
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| [Impacted Files](https://codecov.io/gh/pandas-dev/pandas/pull/20193?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [pandas/core/frame.py](https://codecov.io/gh/pandas-dev/pandas/pull/20193/diff?src=pr&el=tree#diff-cGFuZGFzL2NvcmUvZnJhbWUucHk=) | `97.15% <ø> (ø)` | |

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Thanks @gioiab for the contribution. And sorry it took a while to merge it.