diff --git a/doc/whats-new.rst b/doc/whats-new.rst
index cf56351e44c..f4cf538ea9a 100644
--- a/doc/whats-new.rst
+++ b/doc/whats-new.rst
@@ -18,15 +18,6 @@ What's New
 v0.14.1 (unreleased)
 --------------------
 
-Breaking changes
-~~~~~~~~~~~~~~~~
-
-New functions/methods
-~~~~~~~~~~~~~~~~~~~~~
-
-Enhancements
-~~~~~~~~~~~~
-
 Bug fixes
 ~~~~~~~~~
 
@@ -34,6 +25,14 @@ Bug fixes
   :py:meth:`xarray.core.groupby.DatasetGroupBy.reduce` when reducing over multiple dimensions.
   (:issue:`3402`). By `Deepak Cherian <https://github.com/dcherian/>`_
 
+Documentation
+~~~~~~~~~~~~~
+
+- Fix the documentation of :py:meth:`DataArray.resample` and
+  :py:meth:`Dataset.resample` and explicitly state that a
+  datetime-like dimension is required. (:pull:`3400`)
+  By `Justus Magin <https://github.com/keewis>`_.
+
 .. _whats-new.0.14.0:
 
 v0.14.0 (14 Oct 2019)
diff --git a/xarray/core/common.py b/xarray/core/common.py
index 8313247c743..a762f7fbed9 100644
--- a/xarray/core/common.py
+++ b/xarray/core/common.py
@@ -914,13 +914,16 @@ def resample(
     ):
         """Returns a Resample object for performing resampling operations.
 
-        Handles both downsampling and upsampling. If any intervals contain no
-        values from the original object, they will be given the value ``NaN``.
+        Handles both downsampling and upsampling. The resampled
+        dimension must be a datetime-like coordinate. If any intervals
+        contain no values from the original object, they will be given
+        the value ``NaN``.
 
         Parameters
         ----------
         indexer : {dim: freq}, optional
-            Mapping from the dimension name to resample frequency.
+            Mapping from the dimension name to resample frequency. The
+            dimension must be datetime-like.
         skipna : bool, optional
             Whether to skip missing values when aggregating in downsampling.
         closed : 'left' or 'right', optional
@@ -978,12 +981,18 @@ def resample(
           * time     (time) datetime64[ns] 1999-12-15 1999-12-16 1999-12-17 ...
 
         Limit scope of upsampling method
+
         >>> da.resample(time='1D').nearest(tolerance='1D')
         <xarray.DataArray (time: 337)>
         array([ 0.,  0., nan, ..., nan, 11., 11.])
         Coordinates:
           * time     (time) datetime64[ns] 1999-12-15 1999-12-16 ... 2000-11-15
 
+        See Also
+        --------
+        pandas.Series.resample
+        pandas.DataFrame.resample
+
         References
         ----------