doc changes

deprecate passing non-existing column in .to_excel(..., columns=)

doc/source/advanced.rst

@@ -1009,7 +1009,7 @@ The different indexing operation can potentially change the dtype of a ``Series`
 
    series1 = pd.Series([1, 2, 3])
    series1.dtype
-   res = series1[[0,4]]
+   res = series1.reindex([0, 4])
    res.dtype
    res
 

doc/source/indexing.rst

@@ -335,7 +335,7 @@ Selection By Label
 
 .. warning::
 
-   Starting in 0.21.0, pandas will show a ``FutureWarning`` if indexing with a list-of-lables and not ALL labels are present. In the future
+   Starting in 0.21.0, pandas will show a ``FutureWarning`` if indexing with a list with missing labels. In the future
    this will raise a ``KeyError``. See :ref:`list-like Using loc with missing keys in a list is Deprecated <indexing.deprecate_loc_reindex_listlike>`
 
 pandas provides a suite of methods in order to have **purely label based indexing**. This is a strict inclusion based protocol.
@@ -644,12 +644,12 @@ For getting *multiple* indexers, using ``.get_indexer``
 
 .. _indexing.deprecate_loc_reindex_listlike:
 
-Indexing with missing list-of-labels is Deprecated
---------------------------------------------------
+Indexing with list with missing labels is Deprecated
+----------------------------------------------------
 
 .. warning::
 
-   Starting in 0.21.0, using ``.loc`` or ``[]`` with a list-like containing one or more missing labels, is deprecated, in favor of ``.reindex``.
+   Starting in 0.21.0, using ``.loc`` or ``[]`` with a list with one or more missing labels, is deprecated, in favor of ``.reindex``.
 
 In prior versions, using ``.loc[list-of-labels]`` would work as long as *at least 1* of the keys was found (otherwise it
 would raise a ``KeyError``). This behavior is deprecated and will show a warning message pointing to this section. The
@@ -672,7 +672,6 @@ Previous Behavior
 
 .. code-block:: ipython
 
-
    In [4]: s.loc[[1, 2, 3]]
    Out[4]:
    1    2.0
@@ -683,6 +682,8 @@ Previous Behavior
 
 Current Behavior
 
+.. code-block:: ipython
+
    In [4]: s.loc[[1, 2, 3]]
    Passing list-likes to .loc with any non-matching elements will raise
    KeyError in the future, you can use .reindex() as an alternative.
@@ -720,7 +721,7 @@ Having a duplicated index will raise for a ``.reindex()``:
    s = pd.Series(np.arange(4), index=['a', 'a', 'b', 'c'])
    labels = ['c', 'd']
 
-.. code-block:: python
+.. code-block:: ipython
 
    In [17]: s.reindex(labels)
    ValueError: cannot reindex from a duplicate axis
@@ -734,7 +735,7 @@ axis, and then reindex.
 
 However, this would *still* raise if your resulting index is duplicated.
 
-.. code-block:: python
+.. code-block:: ipython
 
    In [41]: labels = ['a', 'd']
 
@@ -959,7 +960,7 @@ when you don't know which of the sought labels are in fact present:
    s[s.index.isin([2, 4, 6])]
 
    # compare it to the following
-   s[[2, 4, 6]]
+   s.reindex([2, 4, 6])
 
 In addition to that, ``MultiIndex`` allows selecting a separate level to use
 in the membership check:

doc/source/whatsnew/v0.21.0.txt

@@ -270,10 +270,10 @@ We have updated our minimum supported versions of dependencies (:issue:`15206`,
 
 .. _whatsnew_0210.api_breaking.loc:
 
-Indexing with missing list-of-labels is Deprecated
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Indexing with a list with missing labels is Deprecated
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Previously, selecting at least 1 valid label with a list-like indexer would always succeed, returning ``NaN`` for missing labels.
+Previously, selecting with a list of labels, where one or more labels were missing would always succeed, returning ``NaN`` for missing labels.
 This will now show a ``FutureWarning``, in the future this will raise a ``KeyError`` (:issue:`15747`).
 This warning will trigger on a ``DataFrame`` or a ``Series`` for using ``.loc[]``  or ``[[]]`` when passing a list-of-labels with at least 1 missing label.
 See the :ref:`deprecation docs <indexing.deprecate_loc_reindex_listlike>`.
@@ -288,7 +288,6 @@ Previous Behavior
 
 .. code-block:: ipython
 
-
    In [4]: s.loc[[1, 2, 3]]
    Out[4]:
    1    2.0
@@ -299,6 +298,8 @@ Previous Behavior
 
 Current Behavior
 
+.. code-block:: ipython
+
    In [4]: s.loc[[1, 2, 3]]
    Passing list-likes to .loc or [] with any missing label will raise
    KeyError in the future, you can use .reindex() as an alternative.
@@ -628,6 +629,7 @@ Deprecations
 - :func:`SeriesGroupBy.nth` has deprecated ``True`` in favor of ``'all'`` for its kwarg ``dropna`` (:issue:`11038`).
 - :func:`DataFrame.as_blocks` is deprecated, as this is exposing the internal implementation (:issue:`17302`)
 - ``pd.TimeGrouper`` is deprecated in favor of :class:`pandas.Grouper` (:issue:`16747`)
+- Passing a non-existant column in ``.to_excel(..., columns=)`` is deprecated and will raise a ``KeyError`` in the future (:issue:`17295`)
 
 .. _whatsnew_0210.deprecations.argmin_min
 

pandas/io/formats/excel.py

@@ -359,11 +359,18 @@ def __init__(self, df, na_rep='', float_format=None, cols=None,
 
             # all missing, raise
             if not len(Index(cols) & df.columns):
-                raise KeyError
+                raise KeyError(
+                    "passes columns are not ALL present dataframe")
+
+            # deprecatedin gh-17295
+            # 1 missing is ok (for now)
+            if len(Index(cols) & df.columns) != len(cols):
+                warnings.warn(
+                    "columns must be a subset of the "
+                    "dataframe columns; this will raise "
+                    "a KeyError in the future",
+                    FutureWarning)
 
-            # 1 missing is ok
-            # TODO(jreback) this should raise
-            # on *any* missing columns
             self.df = df.reindex(columns=cols)
         self.columns = self.df.columns
         self.float_format = float_format

pandas/tests/io/test_excel.py

@@ -1808,7 +1808,9 @@ def test_invalid_columns(self):
             write_frame = DataFrame({'A': [1, 1, 1],
                                      'B': [2, 2, 2]})
 
-            write_frame.to_excel(path, 'test1', columns=['B', 'C'])
+            with tm.assert_produces_warning(FutureWarning,
+                                            check_stacklevel=False):
+                write_frame.to_excel(path, 'test1', columns=['B', 'C'])
             expected = write_frame.reindex(columns=['B', 'C'])
             read_frame = read_excel(path, 'test1')
             tm.assert_frame_equal(expected, read_frame)