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Shape Chart - X.shape[0] will give the number of rows in an array. 82 yourarray.shape or np.shape() or np.ma.shape() returns the shape of your ndarray as a tuple; (r,) and (r,1) just add (useless) parentheses but still express respectively 1d. When reshaping an array, the new shape must contain the same number of elements. In your case it will give output 10. 10 x[0].shape will give the length of 1st row of an array. Please can someone tell me work of shape [0] and shape [1]? For example the doc says units specify the. And you can get the (number of) dimensions of your array using. It's useful to know the usual numpy.

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(r,) and (r,1) just add (useless) parentheses but still express respectively 1d. Shape is a tuple that gives you an indication of the number of dimensions in the array. In python shape [0] returns the dimension but in this code it is returning total number of set. In your case it will give output 10. And you can get the.

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X.shape[0] will give the number of rows in an array. (r,) and (r,1) just add (useless) parentheses but still express respectively 1d. If you will type x.shape[1], it will. For example the doc says units specify the. It's useful to know the usual numpy.

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In python shape [0] returns the dimension but in this code it is returning total number of set. And you can get the (number of) dimensions of your array using. For example the doc says units specify the. Shape of passed values is (x, ), indices imply (x, y) asked 11 years, 8 months ago modified 7 years, 4 months.

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In your case it will give output 10. (r,) and (r,1) just add (useless) parentheses but still express respectively 1d. In python shape [0] returns the dimension but in this code it is returning total number of set. Shape is a tuple that gives you an indication of the number of dimensions in the array. So in your case, since.

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For example the doc says units specify the. In your case it will give output 10. When reshaping an array, the new shape must contain the same number of elements. Your dimensions are called the shape, in numpy. 10 x[0].shape will give the length of 1st row of an array.

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Instead of calling list, does the size class have some sort of attribute i can access directly to get the shape in a tuple or list form? What numpy calls the dimension is 2, in your case (ndim). Your dimensions are called the shape, in numpy. Shape is a tuple that gives you an indication of the number of dimensions.

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(r,) and (r,1) just add (useless) parentheses but still express respectively 1d. What numpy calls the dimension is 2, in your case (ndim). Shape of passed values is (x, ), indices imply (x, y) asked 11 years, 8 months ago modified 7 years, 4 months ago viewed 60k times Shape is a tuple that gives you an indication of the.

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10 x[0].shape will give the length of 1st row of an array. Your dimensions are called the shape, in numpy. So in your case, since the index value of y.shape[0] is 0, your are working along the first. 82 yourarray.shape or np.shape() or np.ma.shape() returns the shape of your ndarray as a tuple; When reshaping an array, the new shape.

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It's useful to know the usual numpy. For any keras layer (layer class), can someone explain how to understand the difference between input_shape, units, dim, etc.? In your case it will give output 10. When reshaping an array, the new shape must contain the same number of elements. 10 x[0].shape will give the length of 1st row of an array.

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Please can someone tell me work of shape [0] and shape [1]? Shape is a tuple that gives you an indication of the number of dimensions in the array. For example the doc says units specify the. (r,) and (r,1) just add (useless) parentheses but still express respectively 1d. X.shape[0] will give the number of rows in an array.