shape is a tuple that gives you an indication of the number of dimensions in the array. So in your case, since the index value of Y.shape[0] is 0, your are working along the first dimension of …

Shape n, expresses the shape of a 1D array with n items, and n, 1 the shape of a n-row x 1-column array. (R,) and (R,1) just add (useless) parentheses but still express respectively 1D …

Nov 30, 2017 · 82 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 …

Jan 7, 2018 · 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 …

Jul 21, 2018 · 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 = …

You can think of a placeholder in TensorFlow as an operation specifying the shape and type of data that will be fed into the graph.placeholder X defines that an unspecified number of rows of …

Jan 23, 2020 · 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? …

May 24, 2016 · 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 …

I'm creating a plot in ggplot from a 2 x 2 study design and would like to use 2 colors and 2 symbols to classify my 4 different treatment combinations. Currently I have 2 legends, one for …

Feb 14, 2022 · Currently, shape type information is reflected in ndarray.shape. However, most numpy functions that change the dimension or size of an array, however, don't necessarily …