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 …

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 …

Jun 25, 2017 · For any Keras layer (Layer class), can someone explain how to understand the difference between input_shape, units, dim, etc.? For example the doc says units specify the output shape of a …

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 …

Why doesn't Pyspark Dataframe simply store the shape values like pandas dataframe does with .shape? Having to call count seems incredibly resource-intensive for such a common and simple operation.

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 know how to …

Mar 1, 2014 · I'm new to python and numpy in general. I read several tutorials and still so confused between the differences in dim, ranks, shape, aixes and dimensions. My mind seems to be stuck at …

Jan 9, 2014 · 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 …

Aug 16, 2009 · 122 I am trying to set padding in a <shape> declared within an XML file/layout. But whatever I set, nothing changes related to padding. If I modify any other properties, I see the effects …