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author | Christopher Dahlin <christopher@tracsense.tech> | 2021-03-28 15:07:29 +0200 |
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committer | Christopher Dahlin <christopher@tracsense.tech> | 2021-03-28 15:07:29 +0200 |
commit | ddff4415d195ff18cebe565e3538b4690299021d (patch) | |
tree | a6d0ee6b4c2b776a73ec4c8b8843d0f64c97800e /doc/source | |
parent | 18db7880daf6cd20bd7539ab65a3f06663f10d90 (diff) | |
parent | d0794c94932d349d045e773c54c7b0d3d24eebfe (diff) | |
download | numpy-ddff4415d195ff18cebe565e3538b4690299021d.tar.gz |
Merge branch 'main' of https://github.com/cdahlin/numpy into absolute-beginner-doc-clarification
Diffstat (limited to 'doc/source')
-rw-r--r-- | doc/source/user/absolute_beginners.rst | 11 |
1 files changed, 6 insertions, 5 deletions
diff --git a/doc/source/user/absolute_beginners.rst b/doc/source/user/absolute_beginners.rst index 53be9aca8..084bb6d22 100644 --- a/doc/source/user/absolute_beginners.rst +++ b/doc/source/user/absolute_beginners.rst @@ -884,7 +884,8 @@ Indexing and slicing operations are useful when you're manipulating matrices:: >>> data[0, 1] 2 >>> data[1:3] - array([[3, 4]]) + array([[3, 4], + [5, 6]]) >>> data[0:2, 0] array([1, 3]) @@ -893,11 +894,11 @@ Indexing and slicing operations are useful when you're manipulating matrices:: You can aggregate matrices the same way you aggregated vectors:: >>> data.max() - 4 + 6 >>> data.min() 1 >>> data.sum() - 10 + 21 .. image:: images/np_matrix_aggregation.png @@ -905,9 +906,9 @@ You can aggregate all the values in a matrix and you can aggregate them across columns or rows using the ``axis`` parameter:: >>> data.max(axis=0) - array([3, 4]) + array([5, 6]) >>> data.max(axis=1) - array([2, 4]) + array([2, 4, 6]) .. image:: images/np_matrix_aggregation_row.png |