Newaxis contained in
numpy can add one dimension to the original array
np.newaxis produces a different array
depending on where it is placed
one-dimensional array
x = np.random.randint(1, 8, size=5)
x
Out[48]: array([4, 6, 6, 6, 5])
x1 = x[np.newaxis, :]
x1
Out[50]: array([[4, 6, 6, 6, 5]])
x2 = x[:, np.newaxis]
x2
Out[52]:
array([[4],
[6],
[6],
[6],
[5]])
as you can see from the above code,
when putting newaxis first
, which used to be 5, now becomes 1
x span> span> span> span> span> span> span>
< script type=”math/tex” id=”MathJax-Element-124″> \times< /script> 5, so the first dimension has changed, the second dimension has changed
and when you put newaxis in the end, the shape of the new array that you output is 5
x span> span> span> span> span> span> span>
< script type=”math/tex” id=”MathJax-Element-125″> \times< /script> So 1, that’s another dimension that’s less than /p>
So, where you put newaxis, you’ll see an extra dimension in your shape that’s less than /p b>
is as follows:
general problem
is often a problem where you need to take a portion of the data out of the array, that is, take a “slice” or a “strip”
, for example, you need to extract a column
from a two-dimensional array
when you take out the dimension becomes one
if we want to reduce it to two dimensions, we need the above method