REGR: pd.to_hdf(dropna=True) not dropping all nan rows
#### Location of the documentation

[this should provide the location of the documentation, e.g. "pandas.read_csv" or the URL of the documentation, e.g. "https://dev.pandas.io/docs/reference/api/pandas.read_csv.html"]

**Note**: You can check the latest versions of the docs on `master` [here](https://pandas.pydata.org/docs/dev/).

https://pandas.pydata.org/pandas-docs/stable/user_guide/io.html

#### Documentation problem

[this should provide a description of what documentation you believe needs to be fixed/improved]

On the section:

"HDFStore will by default not drop rows that are all missing. This behavior can be changed by setting dropna=True."

The last example:

In [370]: pd.read_hdf('file.h5', 'df_with_missing')
Out[370]: 
   col1  col2
0   0.0   1.0
1   NaN   NaN
2   2.0   NaN

should output:

   col1  col2
0   0.0   1.0
1   2.0   NaN

which does not have rows that are all missing.


#### Suggested fix for documentation

[this should explain the suggested fix and **why** it's better than the existing documentation]

This has been provided above.
