transpose

I got a list of lists in racket and have to transpose them. (: transpose ((list-of(list-of %a)) -> (list-of (list-of %a)))) (check-expect (transpose (list (list 1 2 3) (list 4 5 6))) (list (list 1 4) (list 2 5) (list 3 6))) (define transpose (lambda (xs) (cond ((empty? xs)empty) ((pair? xs)(make-pair (make-pair (first(first xs)) (make-pair (first(first(rest xs)))empty)) (transpose (rest(rest xs)))))))) That's my code at the moment. I think the problem is in the recursive call (correct me if I'm wrong please). The actual outcome is (list (list 1 4)) . The rest seems kinda ignored. It would

I have a 3-D NumPy array, e.g. a = np.random.random((2,3,5)) I would like to transpose the last two axes, i.e. b = a.transpose(0,2,1) However, I do not want a view with twiddled strides! I want to actually copy the array and reorder it in memory . What is the best way to achieve this? The copy() method will reorder to C-contiguous order by default: b = a.transpose(0,2,1).copy() 来源： https://stackoverflow.com/questions/19826262/transpose-array-and-actually-reorder-memory

I have an MS Access database that contains translated sentences in source-target pairs (a translation memory for fellow users of CAT tools). Somewhat annoyingly, source and target are not stored in separate columns, but in rows linked by ID, like this: +---+----+--------------+ |id |lang| text | +---+----+--------------+ 1 a lang a text 1 b lang b text 2 a more a text... 2 b more b text... +---+----+--------------+ What SQL could I use to turn that into a table such as: +---+--------------+--------------+ |id | lang A | lang B | +---+--------------+--------------+ 1 lang a text lang b text 2

For eg - Say I have data in the following format - Current Format I would need the data to be formatted in the following format for ease of use - Required Format Of course the data contains a lot more records - I'm looking for an easy way to transpose data in this way for large sets of data. Any help will be appreciated :) This is very easy with PowerQuery. It is inbuilt for Excel 2016 and a freely available add in for Version from 2010 to 2013. You would set your data up as a table excluding the first row which contains the text Number of Cases (Ctrl + T whilst bring up window to create table

This question already has an answer here: Why apply() returns a transposed xts matrix? 1 answer Apologies, I just realised that this has already been answered here . This should be pretty basic but I do not really understand why it is happening. Can someone help? This is the simple code with the example 'data': applyDirichletPrior <- function (row_vector) { row_vector_added <- row_vector + min (row_vector) row_vector_result <- row_vector_added / sum(row_vector_added) } data <- matrix(c(1,2,3,4,5,6,7,8), nrow=2, ncol=4) applied <- apply(data, 1, function(x) applyDirichletPrior(x)) The output is

My data frame is as follows selection_id last_traded_price 430494 1.46 430494 1.48 430494 1.56 430494 1.57 430495 2.45 430495 2.67 430495 2.72 430495 2.87 I have lots of rows that contain selection id's and I need to keep selection_id column the same but transpose the data in last traded price to look like this. selection_id last_traded_price 430494 1.46 1.48 1.56 1.57 e.t.c 430495 2.45 2.67 2.72 2.87 e.t.c I've tried a to use a pivot (df.pivot(index='selection_id', columns=last_traded_price', values='last_traded_price') Pivot isn't working due to duplicate rows in selection_id. is it possible