cumulative-sum

Say I have data that looks like date, user, items_bought, event_number 2013-01-01, x, 2, 1 2013-01-02, x, 1, 2 2013-01-03, x, 0, 3 2013-01-04, x, 0, 4 2013-01-04, x, 1, 5 2013-01-04, x, 2, 6 2013-01-05, x, 3, 7 2013-01-06, x, 1, 8 2013-01-01, y, 1, 1 2013-01-02, y, 1, 2 2013-01-03, y, 0, 3 2013-01-04, y, 5, 4 2013-01-05, y, 6, 5 2013-01-06, y, 1, 6 to get the cumulative sum per user per data point I was doing data.frame(cum_items_bought=unlist(tapply(as.numeric(data$items_bought), data$user, FUN = cumsum))) output from this looks like date, user, items_bought 2013-01-01, x, 2 2013-01-02, x, 3

How would you do to transform a Column in a table from this: ColumnA ColumnB 2 a 3 b 4 c 5 d 1 a to this: ColumnA ColumnB 3 a 6(=3+3) b 10(=4+3+3) c 15(=5+4+3+3) d I'm interested to see esp. what method you would pick. Mahmoud Gamal Like this: ;WITH cte AS ( SELECT ColumnB, SUM(ColumnA) asum FROM @t gROUP BY ColumnB ), cteRanked AS ( SELECT asum, ColumnB, ROW_NUMBER() OVER(ORDER BY ColumnB) rownum FROM cte ) SELECT (SELECT SUM(asum) FROM cteRanked c2 WHERE c2.rownum <= c1.rownum), ColumnB FROM cteRanked c1; This should give you: ColumnA ColumnB 3 a 6 b 10 c 15 d Here is a live demo I'd

I have a csv string containing doubles (e.g "0.3,0.4,0.3"), and I want to be able to output a double array containing the cumulative sum of these numbers (e.g [0.3,0.7,1.0]). So far, I have double[] probabilities = textBox_f.Text.Split(new char[]{','}).Select(s => double.Parse(s)).ToArray(); which gives the numbers as an array, but not the cumulative sum of the numbers. Is there any way to continue this expression to get what I want, or do I need to use iteration to create a new array from the array I already have? var input=new double[]{ ... } double sum=0; var output=input .Select(w=>sum+=w)

I wrote a short CUDA program that uses the highly-optimized CUB library to demonstrate that one core from an old, quad-core Intel Q6600 processor (all four are supposedly capable of ~30 GFLOPS/sec) can do an inclusive scan (or cumulative/prefix sum if you rather) on 100,000 elements faster than an Nvidia 750 Ti (supposedly capable of 1306 GFLOPS/sec of single precision). Why is this the case? The source code is: #include "cuda_runtime.h" #include "device_launch_parameters.h" #include <cub/cub.cuh> #include <stdio.h> #include <time.h> #include <algorithm> #define gpuErrchk(ans) { gpuAssert((ans

I'm learning to use ggplot2 and am looking for the smallest ggplot2 code that reproduces the base::plot result below. I've tried a few things and they all ended up being horrendously long, so I'm looking for the smallest expression and ideally would like to have the dates on the x-axis (which are not there in the plot below). df = data.frame(date = c(20121201, 20121220, 20130101, 20130115, 20130201), val = c(10, 5, 8, 20, 4)) plot(cumsum(rowsum(df$val, df$date)), type = "l") Try this: ggplot(df, aes(x=1:5, y=cumsum(val))) + geom_line() + geom_point() Just remove geom_point() if you don't want