DOC: NDFrame.to_hdf(data_columns) documented (#13061).

Author: jzwinck

pandas/core/generic.py

@@ -1088,17 +1088,15 @@ def to_json(self, path_or_buf=None, orient=None, date_format='epoch',
                             lines=lines)
 
     def to_hdf(self, path_or_buf, key, **kwargs):
-        """Activate the HDFStore.
+        """Write the contained data to an HDF5 file using HDFStore.
 
         Parameters
         ----------
         path_or_buf : the path (string) or HDFStore object
         key : string
             indentifier for the group in the store
-        mode : optional, {'a', 'w', 'r', 'r+'}, default 'a'
+        mode : optional, {'a', 'w', 'r+'}, default 'a'
 
-          ``'r'``
-              Read-only; no data can be modified.
           ``'w'``
               Write; a new file is created (an existing file with the same
               name would be deleted).
@@ -1116,6 +1114,9 @@ def to_hdf(self, path_or_buf, key, **kwargs):
                        / selecting subsets of the data
         append   : boolean, default False
             For Table formats, append the input data to the existing
+        data_columns : list of columns to create as data columns, or True to
+            use all columns. See
+            `here <http://pandas.pydata.org/pandas-docs/stable/io.html#query-via-data-columns>`__ # noqa
         complevel : int, 1-9, default 0
             If a complib is specified compression will be applied
             where possible
@@ -1126,7 +1127,6 @@ def to_hdf(self, path_or_buf, key, **kwargs):
             If applying compression use the fletcher32 checksum
         dropna : boolean, default False.
             If true, ALL nan rows will not be written to store.
-
         """
 
         from pandas.io import pytables

pandas/io/pytables.py

@@ -859,6 +859,9 @@ def put(self, key, value, format=None, append=False, **kwargs):
         append   : boolean, default False
             This will force Table format, append the input data to the
             existing.
+        data_columns : list of columns to create as data columns, or True to
+            use all columns. See
+            `here <http://pandas.pydata.org/pandas-docs/stable/io.html#query-via-data-columns>`__ # noqa
         encoding : default None, provide an encoding for strings
         dropna   : boolean, default False, do not write an ALL nan row to
             the store settable by the option 'io.hdf.dropna_table'
@@ -936,14 +939,16 @@ def append(self, key, value, format=None, append=True, columns=None,
         append       : boolean, default True, append the input data to the
             existing
         data_columns : list of columns to create as data columns, or True to
-            use all columns
+            use all columns. See
+            `here <http://pandas.pydata.org/pandas-docs/stable/io.html#query-via-data-columns>`__ # noqa
         min_itemsize : dict of columns that specify minimum string sizes
         nan_rep      : string to use as string nan represenation
         chunksize    : size to chunk the writing
         expectedrows : expected TOTAL row size of this table
         encoding     : default None, provide an encoding for strings
         dropna       : boolean, default False, do not write an ALL nan row to
             the store settable by the option 'io.hdf.dropna_table'
+
         Notes
         -----
         Does *not* check if data being appended overlaps with existing