diff options
Diffstat (limited to 'doc')
| -rw-r--r-- | doc/neps/missing-data.rst | 4 | ||||
| -rw-r--r-- | doc/release/2.0.0-notes.rst | 12 |
2 files changed, 11 insertions, 5 deletions
diff --git a/doc/neps/missing-data.rst b/doc/neps/missing-data.rst index 478fe81bc..49528da41 100644 --- a/doc/neps/missing-data.rst +++ b/doc/neps/missing-data.rst @@ -477,7 +477,7 @@ Some examples:: >>> np.sum(a, skipna=True) 11.0 >>> np.mean(a) - NA('<f8') + NA(dtype='<f8') >>> np.mean(a, skipna=True) 3.6666666666666665 @@ -487,7 +487,7 @@ Some examples:: >>> np.max(a, skipna=True) array(NA, dtype='<f8', maskna=True) >>> np.mean(a) - NA('<f8') + NA(dtype='<f8') >>> np.mean(a, skipna=True) /home/mwiebe/virtualenvs/dev/lib/python2.7/site-packages/numpy/core/fromnumeric.py:2374: RuntimeWarning: invalid value encountered in double_scalars return mean(axis, dtype, out) diff --git a/doc/release/2.0.0-notes.rst b/doc/release/2.0.0-notes.rst index 0ba7594fe..d50797cb3 100644 --- a/doc/release/2.0.0-notes.rst +++ b/doc/release/2.0.0-notes.rst @@ -26,9 +26,10 @@ What works with NA: * Basic indexing and slicing, as well as full boolean mask indexing. * All element-wise ufuncs. * UFunc.reduce methods, with a new skipna parameter. + * The nditer object. * Array methods: + ndarray.clip, ndarray.min, ndarray.max, ndarray.sum, ndarray.prod, - ndarray.conjugate, ndarray.diagonal + ndarray.conjugate, ndarray.diagonal, ndarray.flatten + numpy.concatenate, numpy.column_stack, numpy.hstack, numpy.vstack, numpy.dstack @@ -36,6 +37,8 @@ What doesn't work with NA: * Fancy indexing, such as with lists and partial boolean masks. * ndarray.flat and any other methods that use the old iterator mechanism instead of the newer nditer. + * Struct dtypes, which will have corresponding struct masks with + one mask value per primitive field of the struct dtype. * UFunc.reduce of multi-dimensional arrays, with skipna=True and a ufunc that doesn't have an identity. * UFunc.accumulate, UFunc.reduceat. @@ -43,7 +46,10 @@ What doesn't work with NA: rules NA | True == True and NA & False == False yet. * Array methods: + ndarray.argmax, ndarray.argmin, - + numpy.repeat + + numpy.repeat, numpy.delete (relies on fancy indexing), + numpy.append, numpy.insert (relies on fancy indexing), + numpy.where, + Custom formatter for printing arrays @@ -66,7 +72,7 @@ where possible, and performs much faster as well. The function np.concatenate tries to match the layout of its input arrays. Previously, the layout did not follow any particular reason, -and depended in an undesirable on the particular axis chosen for +and depended in an undesirable way on the particular axis chosen for concatenation. A bug was also fixed which silently allowed out of bounds axis arguments. |