Improve quantile method docstring + error (#6939)

* add comment to setup.cfg that numpy >= 1.22 is recommended

* improve docstring and error message for quantile with numpy <1.22

* improve error msg

* Add forgotten f string prefix

Co-authored-by: Mathias Hauser <mathause@users.noreply.github.com>

Co-authored-by: Mathias Hauser <mathause@users.noreply.github.com>

Author: headtr1ck

setup.cfg

@@ -75,7 +75,7 @@ zip_safe = False  # https://mypy.readthedocs.io/en/latest/installed_packages.htm
 include_package_data = True
 python_requires = >=3.8
 install_requires =
-    numpy >= 1.19
+    numpy >= 1.19  # recommended to use >= 1.22 for full quantile method support
     pandas >= 1.2
     packaging >= 20.0
 

xarray/core/dataarray.py

@@ -3920,19 +3920,20 @@ def quantile(
                 8. "median_unbiased" (*)
                 9. "normal_unbiased" (*)
 
-            The first three methods are discontiuous.  The following discontinuous
+            The first three methods are discontiuous. The following discontinuous
             variations of the default "linear" (7.) option are also available:
 
                 * "lower"
                 * "higher"
                 * "midpoint"
                 * "nearest"
 
-            See :py:func:`numpy.quantile` or [1]_ for details. Methods marked with
-            an asterix require numpy version 1.22 or newer. The "method" argument was
-            previously called "interpolation", renamed in accordance with numpy
+            See :py:func:`numpy.quantile` or [1]_ for details. The "method" argument
+            was previously called "interpolation", renamed in accordance with numpy
             version 1.22.0.
 
+            (*) These methods require numpy version 1.22 or newer.
+
         keep_attrs : bool or None, optional
             If True, the dataset's attributes (`attrs`) will be copied from
             the original object to the new one.  If False (default), the new

xarray/core/dataset.py

@@ -6738,11 +6738,12 @@ def quantile(
                 * "midpoint"
                 * "nearest"
 
-            See :py:func:`numpy.quantile` or [1]_ for a description. Methods marked with
-            an asterix require numpy version 1.22 or newer. The "method" argument was
-            previously called "interpolation", renamed in accordance with numpy
+            See :py:func:`numpy.quantile` or [1]_ for details. The "method" argument
+            was previously called "interpolation", renamed in accordance with numpy
             version 1.22.0.
 
+            (*) These methods require numpy version 1.22 or newer.
+
         keep_attrs : bool, optional
             If True, the dataset's attributes (`attrs`) will be copied from
             the original object to the new one.  If False (default), the new

xarray/core/variable.py

@@ -2066,11 +2066,12 @@ def quantile(
                 * "midpoint"
                 * "nearest"
 
-            See :py:func:`numpy.quantile` or [1]_ for details. Methods marked with
-            an asterix require numpy version 1.22 or newer. The "method" argument was
-            previously called "interpolation", renamed in accordance with numpy
+            See :py:func:`numpy.quantile` or [1]_ for details. The "method" argument
+            was previously called "interpolation", renamed in accordance with numpy
             version 1.22.0.
 
+            (*) These methods require numpy version 1.22 or newer.
+
         keep_attrs : bool, optional
             If True, the variable's attributes (`attrs`) will be copied from
             the original object to the new one.  If False (default), the new
@@ -2141,6 +2142,10 @@ def _wrapper(npa, **kwargs):
         if Version(np.__version__) >= Version("1.22.0"):
             kwargs = {"q": q, "axis": axis, "method": method}
         else:
+            if method not in ("linear", "lower", "higher", "midpoint", "nearest"):
+                raise ValueError(
+                    f"Interpolation method '{method}' requires numpy >= 1.22 or is not supported."
+                )
             kwargs = {"q": q, "axis": axis, "interpolation": method}
 
         result = apply_ufunc(