TST: missingdata: Finish up NA mask tests for np.std and np.var

2 files changed, 36 insertions, 2 deletions

diff --git a/doc/release/2.0.0-notes.rst b/doc/release/2.0.0-notes.rst
index ca9bc4147..40ad029f0 100644
--- a/doc/release/2.0.0-notes.rst
+++ b/doc/release/2.0.0-notes.rst
@@ -11,7 +11,6 @@ Highlights
 New features
 ============
 
-
 Mask-based NA missing values
 ----------------------------
 
@@ -31,7 +30,8 @@ What works with NA:
        + ndarray.clip, ndarray.min, ndarray.max, ndarray.sum, ndarray.prod,
          ndarray.conjugate, ndarray.diagonal, ndarray.flatten
        + numpy.concatenate, numpy.column_stack, numpy.hstack,
-         numpy.vstack, numpy.dstack, numpy.squeeze
+         numpy.vstack, numpy.dstack, numpy.squeeze, numpy.mean, numpy.std,
+         numpy.var
 
 What doesn't work with NA:
     * Fancy indexing, such as with lists and partial boolean masks.
@@ -63,6 +63,22 @@ Differences with R:
       This may have a practical advantage in spite of violating the
       NA theoretical model, so NumPy could adopt the behavior if necessary
 
+Reduction UFuncs Generalize axis= Parmaeter
+-------------------------------------------
+
+Any ufunc.reduce function call, as well as other reductions like
+sum, prod, any, all, max and min support the ability to choose
+a subset of the axes to reduce over. Previously, one could say
+axis=None to mean all the axes or axis=# to pick a single axis.
+Now, one can also say axis=(#,#) to pick a list of axes for reduction.
+
+Reduction UFuncs New keepdims= Parameter
+----------------------------------------
+
+There is a new keepdims= parameter, which if set to True, doesn't
+throw away the reduction axes but instead sets them to have size one.
+when this option is set, the reduction result will broadcast correctly
+to the original operand which was reduced.
 
 
 Custom formatter for printing arrays
diff --git a/numpy/core/tests/test_maskna.py b/numpy/core/tests/test_maskna.py
index ad80f403d..e284f841b 100644
--- a/numpy/core/tests/test_maskna.py
+++ b/numpy/core/tests/test_maskna.py
@@ -1132,6 +1132,24 @@ def test_array_maskna_var_std():
     res = np.std(a, axis=1)
     assert_array_almost_equal(res, [np.NA, 0.81649658092772603])
 
+    # With an NA and skipna=True
+    a = np.arange(6, maskna=True).reshape(2,3)
+    a[0,1] = np.NA
+
+    res = np.var(a, skipna=True)
+    assert_almost_equal(res, 2.96)
+    res = np.std(a, skipna=True)
+    assert_almost_equal(res, 1.7204650534085253)
+
+    res = np.var(a, axis=0, skipna=True)
+    assert_array_equal(res, [2.25, 0, 2.25])
+    res = np.std(a, axis=0, skipna=True)
+    assert_array_equal(res, [1.5, 0, 1.5])
+
+    res = np.var(a, axis=1, skipna=True)
+    assert_array_almost_equal(res, [1.0, 0.66666666666666663])
+    res = np.std(a, axis=1, skipna=True)
+    assert_array_almost_equal(res, [1.0, 0.81649658092772603])
 
 if __name__ == "__main__":
     run_module_suite()