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 your array.

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 and 2D array …

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 demo with some …

Sep 9, 2013 · The criterion to satisfy for providing the new shape is that 'The new shape should be compatible with the original shape' numpy allow us to give one of new shape parameter as -1 (eg: (2, …

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 = …

Nov 30, 2017 · 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(). …

Jan 29, 2021 · I'm trying to find out how this above-mentioned piece of code works in a layman sense? for context, this code contains Numpy, Seaborn, Pandas and matplotlib. below is the line of code: …

Jan 25, 2017 · I am trying to add a shape at a specific cell location but cannot get the shape added at the desired location for some reason. Below is the code I am using to add the shape: …

ValueError: shape mismatch: objects cannot be broadcast to a single shape Asked 12 years, 11 months ago Modified 2 years, 3 months ago Viewed 300k times

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 dimensions, for a …