In : a = np.random.random((3,3))
In : a
Out:
array([[ 0.30462663, 0.36803408, 0.69629604],
[ 0.35804978, 0.74850708, 0.18725215],
[ 0.90304957, 0.14432893, 0.13858149]])
In : a.min()
Out: 0.1385814930772824
In : a.max()
Out: 0.90304957398425356
In : a.sum()
Out: 3.8487257463334474
In : a.mean()
Out: 0.42763619403704972
In : a.var()
Out: 0.07180891826216837
In : a.std()
Out: 0.26797186095216857
In : np.median(a)
Out: 0.3580497822916181
Applying aggregate functions on specific axes
In : a = np.arange(6).reshape(3,2)
In : a
Out:
array([[0, 1],
[2, 3],
[4, 5]])
In : a.sum(axis=0)
Out: array([6, 9])
In : a.sum(axis=1)
Out: array([1, 5, 9])
