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| author | Nathaniel J. Smith <njs@pobox.com> | 2017-09-07 17:33:50 -0700 |
|---|---|---|
| committer | Nathaniel J. Smith <njs@pobox.com> | 2017-09-07 17:33:50 -0700 |
| commit | a373d19512526e3e7c63823c39adeb75a47a983c (patch) | |
| tree | 4265ca389a06202aa4c29b429c616abb23660c7c /doc/source/user | |
| parent | 6810e1e9015538bf030d7e307f11f0828e3dacbe (diff) | |
| download | numpy-a373d19512526e3e7c63823c39adeb75a47a983c.tar.gz | |
DOC: clarify wording in tutorial
In gh-9664, a user got confused by this wording, because they thought
it was talking about the length of a vector as a distance in cartesian
space versus the length of a vector as the number of elements it
contains.
Diffstat (limited to 'doc/source/user')
| -rw-r--r-- | doc/source/user/quickstart.rst | 10 |
1 files changed, 5 insertions, 5 deletions
diff --git a/doc/source/user/quickstart.rst b/doc/source/user/quickstart.rst index f37e255bc..87b0de2af 100644 --- a/doc/source/user/quickstart.rst +++ b/doc/source/user/quickstart.rst @@ -28,11 +28,11 @@ table of elements (usually numbers), all of the same type, indexed by a tuple of positive integers. In NumPy dimensions are called *axes*. The number of axes is *rank*. -For example, the coordinates of a point in 3D space ``[1, 2, 1]`` is an -array of rank 1, because it has one axis. That axis has a length of 3. -In the example pictured below, the array has rank 2 (it is 2-dimensional). -The first dimension (axis) has a length of 2, the second dimension has a -length of 3. +For example, the coordinates of a point in 3D space ``[1, 2, 1]`` is +an array of rank 1, because it has one axis. That axis has 3 elements +in it, so we say it has a length of 3. In the example pictured +below, the array has rank 2 (it is 2-dimensional). The first dimension +(axis) has a length of 2, the second dimension has a length of 3. :: |