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| author | Ross Barnowski <rossbar@berkeley.edu> | 2021-10-14 13:35:09 -0700 |
|---|---|---|
| committer | Ross Barnowski <rossbar@berkeley.edu> | 2021-10-14 13:35:09 -0700 |
| commit | 707985360ac671006951b2d39dceef9ba6e38cae (patch) | |
| tree | 65cbc6116263c1bcf64ae72a633b3321b11e417f | |
| parent | d03e7887e12f9e9041113658775ba8cc478d5c58 (diff) | |
| download | numpy-707985360ac671006951b2d39dceef9ba6e38cae.tar.gz | |
Add missing indefinite article.
| -rw-r--r-- | doc/source/user/absolute_beginners.rst | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/doc/source/user/absolute_beginners.rst b/doc/source/user/absolute_beginners.rst index 7b9e33232..a98ca3e40 100644 --- a/doc/source/user/absolute_beginners.rst +++ b/doc/source/user/absolute_beginners.rst @@ -900,7 +900,7 @@ You can aggregate matrices the same way you aggregated vectors:: You can aggregate all the values in a matrix and you can aggregate them across columns or rows using the ``axis`` parameter. To illustrate this point, let's -look at slightly modified dataset:: +look at a slightly modified dataset:: >>> data = np.array([[1, 2], [5, 3], [4, 6]]) >>> data |