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| author | Ross Barnowski <rossbar@berkeley.edu> | 2022-09-27 14:27:23 -0700 |
|---|---|---|
| committer | Ross Barnowski <rossbar@berkeley.edu> | 2022-09-27 14:27:23 -0700 |
| commit | f32c3e61d34235e4bc8833cbc364ac7451b4074e (patch) | |
| tree | 6657daa32ef51bd28e38f8150631622bb037dbcf /numpy/core/fromnumeric.py | |
| parent | b034f6dc33ebfef2e389a7b011c7b7920cc44f68 (diff) | |
| download | numpy-f32c3e61d34235e4bc8833cbc364ac7451b4074e.tar.gz | |
DOC: Apply Chuck's suggestion.
Co-authored-by: Charles Harris <charlesr.harris@gmail.com>
Diffstat (limited to 'numpy/core/fromnumeric.py')
| -rw-r--r-- | numpy/core/fromnumeric.py | 10 |
1 files changed, 5 insertions, 5 deletions
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py index fda4d71e0..6e463f409 100644 --- a/numpy/core/fromnumeric.py +++ b/numpy/core/fromnumeric.py @@ -3036,16 +3036,16 @@ def prod(a, axis=None, dtype=None, out=None, keepdims=np._NoValue, Even when the input array is two-dimensional: - >>> np.prod([[1.,2.],[3.,4.]]) + >>> a = np.array([[1., 2.], [3., 4.]]) + >>> np.prod(a) 24.0 But we can also specify the axis over which to multiply: - >>> np.prod([[1.,2.],[3.,4.]], axis=1) + >>> np.prod(a, axis=1) array([ 2., 12.]) - - >>> np.prod([[1.,2.,3.],[3.,4.,5.],[1.,3.,5.]], axis=0) - array([ 3., 24., 75.]) + >>> np.prod(a, axis=0) + array([3., 8.]) Or select specific elements to include: |