On 30 Dec 2017, at 5:38 pm, Vinodhini Balusamy <me.vi...@gmail.com> wrote: > > Just one more question from the details you have provided which from my > understanding strongly seems to be Design > [DEREK] You cannot create a regular 2-dimensional integer array from one row > of length 3 >> and a second one of length 0. Thus np.array chooses the next most basic type >> of >> array it can fit your input data in > Indeed, the general philosophy is to preserve the structure and type of your input data as far as possible, i.e. a list is turned into a 1d-array, a list of lists (or tuples etc…) into a 2d-array,_ if_ the sequences are of equal length (even if length 1). As long as there is an unambiguous way to convert the data into an array (see below).
> Which is the case, only if an second one of length 0 is given. > What about the case 1 : > >>> x12 = np.array([[1,2,3]]) > >>> x12 > array([[1, 2, 3]]) > >>> print(x12) > [[1 2 3]] > >>> x12.ndim > 2 > >>> > >>> > This seems to take 2 dimension. Yes, structurally this is equivalent to your second example > also, >>> x12 = np.array([[1,2,3],[0,0,0]]) >>> print(x12) [[1 2 3] [0 0 0]] >>> x12.ndim 2 > I presumed the above case and the case where length 0 is provided to be > treated same(I mean same behaviour). > Correct me if I am wrong. > In this case there is no unambiguous way to construct the array - you would need a shape (2, 3) array to store the two lists with 3 elements in the first list. Obviously x12[0] would be np.array([1,2,3]), but what should be the value of x12[1], if the second list is empty - it could be zeros, or repeating x12[0], or simply undefined. np.array([1, 2, 3], [4]]) would be even less clearly defined. These cases where there is no obvious “right” way to create the array have usually been discussed at some length, but I don’t know if this is fully documented in some place. For the essentials, see https://docs.scipy.org/doc/numpy/reference/routines.array-creation.html note also the upcasting rules if you have e.g. a mix of integers and reals or complex numbers, and also how to control shape or data type explicitly with the respective keywords. Derek _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
