DOC: Table about how plots handle missing data.

Author: TomAugspurger

doc/source/visualization.rst

@@ -203,13 +203,6 @@ To get horizontal bar plots, pass ``kind='barh'``:
    @savefig barh_plot_stacked_ex.png
    df2.plot(kind='barh', stacked=True);
 
-Pandas tries to be pragmatic about plotting DataFrames or Series
-that contain missing data. When it makes sense missing values will
-be filled with 0 (as is the case with bar plots). For other plots,
-like line plots, filling in 0 usually doesn't make sense, and so pandas doesn't
-try to guess. If you want to be explicit you can always call
-:meth:`~pandas.DataFrame.fillna` before plotting.
-
 .. _visualization.hist:
 
 Histograms
@@ -684,6 +677,44 @@ See the `matplotlib pie documenation <http://matplotlib.org/api/pyplot_api.html#
 
     plt.close('all')
 
+.. _visualization.missing_data
+
+Plotting with Missing Data
+--------------------------
+
+Pandas tries to be pragmatic about plotting DataFrames or Series
+that contain missing data. Missing values are dropped, left out, or filled
+depending on the plot type.
+
++----------------+--------------------------------------+
+| Plot Type      | NaN Handling                         |
++================+======================================+
+| Line           | Leave gaps at NaNs                   |
++----------------+--------------------------------------+
+| Line (stacked) | Fill 0's                             |
++----------------+--------------------------------------+
+| Bar            | Fill 0's                             |
++----------------+--------------------------------------+
+| Scatter        | Drop NaNs                            |
++----------------+--------------------------------------+
+| Histogram      | Drop NaNs (column-wise)              |
++----------------+--------------------------------------+
+| Box            | Drop NaNs (column-wise)              |
++----------------+--------------------------------------+
+| Area           | Fill 0's                             |
++----------------+--------------------------------------+
+| KDE            | Drop NaNs (column-wise)              |
++----------------+--------------------------------------+
+| Hexbin         | Drop NaNs                            |
++----------------+--------------------------------------+
+| Pie            | Fill 0's                             |
++----------------+--------------------------------------+
+
+If any of these defaults are not what you want, or if you want to be
+explicit about how missing values are handled, consider using
+:meth:`~pandas.DataFrame.fillna` or :meth:`~pandas.DataFrame.dropna`
+before plotting.
+
 .. _visualization.tools:
 
 Plotting Tools