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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
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
android - How to set shapes opacity? - Stack Overflow I already know how to set the opacity of the background image but I need to set the opacity of my shape object In my Android app, I have it like this: and I want to make this black area a bit
python - Keras Dense layer Output Shape - Stack Overflow For example, output shape of Dense layer is based on units defined in the layer where as output shape of Conv layer depends on filters Another thing to remember is, by default, last dimension of any input is considered as number of channel
python - list object has no attribute shape - Stack Overflow 8 list object in python does not have 'shape' attribute because 'shape' implies that all the columns (or rows) have equal length along certain dimension Let's say list variable a has following properties:
python - shape vs len for numpy array - Stack Overflow Still, performance-wise, the difference should be negligible except for a giant giant 2D dataframe So in line with the previous answers, df shape is good if you need both dimensions, for a single dimension, len() seems more appropriate conceptually Looking at property vs method answers, it all points to usability and readability of code