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| author | Mark Wiebe <mwwiebe@gmail.com> | 2011-08-25 21:47:27 -0700 |
|---|---|---|
| committer | Charles Harris <charlesr.harris@gmail.com> | 2011-08-27 07:27:01 -0600 |
| commit | cc326304a60c35d38dc29adf2544a29d6dcedfee (patch) | |
| tree | 2dfe5b1d41bff282e76286558651b9f784ec3528 /doc/neps | |
| parent | a43d255dbc243ea7910e1b92ba83704e1a880c70 (diff) | |
| download | numpy-cc326304a60c35d38dc29adf2544a29d6dcedfee.tar.gz | |
ENH: missingdata: Make numpy.all follow the NA && False == False rule
Diffstat (limited to 'doc/neps')
| -rw-r--r-- | doc/neps/missing-data.rst | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/doc/neps/missing-data.rst b/doc/neps/missing-data.rst index 51b02e6ab..6efdf0fa1 100644 --- a/doc/neps/missing-data.rst +++ b/doc/neps/missing-data.rst @@ -240,7 +240,7 @@ NA dtype versions respectively. The np.NA singleton may accept a dtype= keyword parameter, indicating that it should be treated as an NA of a particular data type. This is also a mechanism for preserving the dtype in a NumPy scalar-like fashion. -Here's what this could look like:: +Here's what this looks like:: >>> np.sum(np.array([1.0, 2.0, np.NA, 7.0], maskna=True)) NA(dtype='<f8') |