- Whatsnew section added

- Documentation section added

Author: ischurov

doc/source/timeseries.rst

@@ -457,22 +457,6 @@ We are stopping on the included end-point as it is part of the index
 
    dft['2013-1-15':'2013-1-15 12:30:00']
 
-.. warning::
-
-   The following selection will raise a ``KeyError``; otherwise this selection methodology
-   would be inconsistent with other selection methods in pandas (as this is not a *slice*, nor does it
-   resolve to one)
-
-   .. code-block:: python
-
-      dft['2013-1-15 12:30:00']
-
-   To select a single row, use ``.loc``
-
-   .. ipython:: python
-
-      dft.loc['2013-1-15 12:30:00']
-
 .. versionadded:: 0.18.0
 
 DatetimeIndex Partial String Indexing also works on DataFrames with a ``MultiIndex``. For example:
@@ -491,6 +475,45 @@ DatetimeIndex Partial String Indexing also works on DataFrames with a ``MultiInd
    dft2 = dft2.swaplevel(0, 1).sort_index()
    dft2.loc[idx[:, '2013-01-05'], :]
 
+String Indexing: slice vs. exact match
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+The same string used as an indexing parameter can be treated either as slice or as exact match depending on the resolution of an index. If the string is less precise than index, it will be treated as a slice, otherwise as an exact match.
+
+.. ipython:: python
+    series_minute = pd.Series([1, 2, 3], DatetimeIndex(['2011-12-31 23:59:00',
+                                                        '2012-01-01 00:00:00',
+                                                        '2012-01-01 00:01:00']))
+    series_minute.index.resolution
+    series_minute['2011-12-31 23'] # returns Series
+    series_minute['2012-12-31 23:59'] # returns scalar
+
+    series_second = pd.Series([1, 2, 3], DatetimeIndex(['2011-12-31 23:59:59',
+                                                        '2012-01-01 00:00:00',
+                                                        '2012-01-01 00:00:01']))
+    series_second.index.resolution
+    series_second['2012-12-31 23:59'] # now it returns scalar
+
+It also works for ``DataFrame``:
+
+.. ipython:: python
+    dft_minute = pd.DataFrame(series_minute)
+    dft_minute['2011-12-31 23']
+
+.. warning::
+
+   If a string used in ``DataFrame``'s ``[]`` indexing is treated as an exact match the selection will be column-wise and not row-wise. This is consistent with :ref:`Indexing Basics <indexing.basics>`. For example, the following code will raise ``KeyError`` as there is no column with index ``'2012-12-31 23:59'``:
+
+   .. code-block:: python
+
+      df_minute['2012-12-31 23:59']
+
+   To select a single row, use ``.loc``
+
+   .. ipython:: python
+
+      df_minute.loc['2012-12-31 23:59']
+
 Datetime Indexing
 ~~~~~~~~~~~~~~~~~
 

doc/source/whatsnew/v0.20.0.txt

@@ -70,6 +70,38 @@ Backwards incompatible API changes
 Other API Changes
 ^^^^^^^^^^^^^^^^^
 
+- :ref:`DatetimeIndex Partial String Indexing <timeseries.partialindexing>` now works as exact match provided that string resolution coincides with index resolution (:issue:`14826`).
+
+  .. ipython:: python
+
+    df = DataFrame({'a': [1, 2, 3]}, DatetimeIndex(['2011-12-31 23:59:59',
+                                                    '2012-01-01 00:00:00',
+                                                    '2012-01-01 00:00:01']))
+  Previous Behavior:
+
+  .. code-block:: ipython
+
+    In [4]: df['2011-12-31 23:59:59']
+    Out[4]:
+                         a
+    2011-12-31 23:59:59  1
+
+    In [5]: df['a']['2011-12-31 23:59:59']
+    Out[5]:
+    2011-12-31 23:59:59    1
+    Name: a, dtype: int64
+
+
+  New Behavior:
+
+  .. code-block:: ipython
+
+    In [4]: df['2011-12-31 23:59:59']
+    KeyError: '2011-12-31 23:59:59'
+
+    In [5]: df['a']['2011-12-31 23:59:59']
+    Out[5]: 1
+
 .. _whatsnew_0200.deprecations:
 
 Deprecations