arrays - what does numpy ndarray shape do? - Stack Overflow yourarray shape or np shape() or np ma shape() returns the shape of your ndarray as a tuple; And you can get the (number of) dimensions of your array using yourarray ndim or np ndim() (i e it gives the n of the ndarray since all arrays in NumPy are just n-dimensional arrays (shortly called as ndarray s)) For a 1D array, the shape would be (n,) where n is the number of elements in your array
What does shape[0] and shape[1] do in python? - Stack Overflow In python shape[0] returns the dimension but in this code it is returning total number of set Please can someone tell me work of shape[0] and shape[1]? Code: m_train = train_set_x_orig shape[0]
python - x. shape [0] vs x [0]. shape in NumPy - Stack Overflow On the other hand, x shape is a 2-tuple which represents the shape of x, which in this case is (10, 1024) x shape[0] gives the first element in that tuple, which is 10 Here's a demo with some smaller numbers, which should hopefully be easier to understand
shape = 19, shape = 20 and shape=16 in R graphics [duplicate] In R graphics and ggplot2 we can specify the shape of the points I am wondering what is the main difference between shape = 19, shape = 20 and shape = 16? Is it the size? This post might consider
How to import convert SVG to native Draw. io shape? [closed] For example on the this screenshot I have to the left a imported SVG and on the right a regular Draw io shape You can see that for the SVG, I can only edit Fill cls-1 or Line cls-1, but for the second shape, I can associate a style: Is there a method to transform an SVG into native Draw io shapes, enabling style application?
numpy: size vs. shape in function arguments? - Stack Overflow Shape (in the numpy context) seems to me the better option for an argument name The actual relation between the two is size = np prod(shape) so the distinction should indeed be a bit more obvious in the arguments names
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