similar to: Transform dataframe

Hi R-users I have a data set. There are 10 products and the numbers of people who ranked the products. The format of the data set is productID rank1 rank2 rank3 rank4 rank5 rank6 rank7 rank8 rank9 rank10 ------------------------------------------------------------------------------------------------------- 1 10 2 3 3 6 4 2 5

Dear R groups: I have the data as follows, I want to plot the "Rank1 ~ obs30*Cases" and "Rank2 ~ obs30*Cases" on the same plot as one 3-D scatter plot, how to do that? Any help is highly appreciated. ID obs30 Cases RANK1 RANK2 1 0.03175 63 82 81 2 0.00000 34 1 34 3 0.00000 36 2 41 4 0.00000 54 3 26 5 0.00000 22 4 42 6 0.00746 134 39 32 7 0.00000 2 5 53 8 0.01190 168 46 31

Hi, I recently ran into the problem that I needed a Siegel-Tukey test for equal variability based on ranks. Maybe there is a package that has it implemented, but I could not find it. So I programmed an R function to do it. The Siegel-Tukey test requires to recode the ranks so that they express variability rather than ascending order. This is essentially what the code further below does. After the

I'm sure this is a simple task, but how to do it has escaped me. I have imported data from two separate files (each file contains the results from an information retrieval algorithm) organized into a list. They are organized by File,Query, and Rank (in that order): [[1]] Doc Query Rank 5 1 1 9 1 2 7 1 3 5 2 1 7 2 2 9 2 3 [[2]]

I have a matrix like this Name 1 2 3 4 5 NM_001039514 1.033557047 0.7469879518 0.9004524887 0.8613861386 0.7952499048 NM_001039723 1.0759493671 1.2315789474 0.8666666667 1.1142857143 0.9428011471 NM_001042605 0.9897435897 0.8870431894

Hi, I ran into a problem where I actually need rank(, ties.method="last"). It would be great to have this feature in base and it's also simple to get (see below). Thanks & cheers, Marius rank2 <- function (x, na.last = TRUE, ties.method = c("average", "first", "last", # new "last" "random", "max",

Hi All I was wondering how to get the same results with gls and lme. In my lme, the design matrix for the random effects is (should be) a identity matrix and therefore G should add up with R to produce the R matrix that gls would report (V=ZGZ'+R). Added complexity is that I have 3 levels, so I have R, G and say H (V=WHW'+ZGZ'+R). The lme is giving me the correct results, I am

Hi, I am using Spark and the Sparklyr library in R. I have a file with several lines. For example A B C awer.ttp.net Code 554 abcd.ttp.net Code 747 asdf.ttp.net Part 554 xyz.ttp.net Part 747 I want to split just column A of the table and I want a new row added to the table D, with values awe, abcd, asdf, and xyz. I am trying to use a command in

Rows are horizontal, columns are vertical. You really need to spend some time with an R tutorial. dta <- read.table( "yourfile", header=TRUE, as.is=TRUE ) dta2 <- dta dta2$D <- c( "awe", "abcd", "asdf", "xyz" ) dta2 <- dta2[ , c( "A", "D" ) ] -- Sent from my phone. Please excuse my brevity. On June 22, 2017

I'm sorry for the really vague subject line but I am not sure how to succinctly describe what I am doing and what the problem is. But, here goes: 1. I have data with two-way data with frequencies. Below is an example, though in reality I am looking at about 10 different variables that I am crossing so the values of X1 and X2 change. X1 and X2 are place holders. Here's the dataset

Hello all, I have a .csv file like below. Tool,Step_Number,Data1,Data2... etc up to 100 columns. A,1,0,1 A,2,3,1 A,3,2,1 . . B,1,3,2 B,2,1,2 B,3,3,2 . . ...... so on upto 50 rows where the column "*Tool*" has distinct steps in second column "*Step_Number*",but both have same entries in Step_Number column. I want the output like below.

Marius Hofert-4------------------------------ > Den 2015-10-09 kl. 12:14, skrev Martin Maechler: > I think so: the code above doesn't seem to do the right thing. Consider > the following example: > > > x <- c(1, 1, 2, 3) > > rank2(x, ties.method = "last") > [1] 1 2 4 3 > > That doesn't look right to me -- I had expected > > >

Dear all, I have a data (bellow) and I want to make a correlation test with p-value structure(list(Name = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("CTJ", "PKR", "TTK"), class = "factor"), score = c(86.4371428571428, 89.7028571428572, 87.728, 89.99, 89.42, 85.6914285714286, 82.256,

Hi Jeff, Thank you for the suggestions -- I appreciate your help. Unfortunately, the result2 has two problems... (1) there are now 3 date columns (it looks like 2 cols are merged into 1 col) (2) the output rows should not have any of the basistime dates repeated (maybe I misstated the problem); I need the max fcst value by basistime, but also list the date value for that row; for example:

I am trying to create a barplot displaying the sums of 2 columns of data grouped by a variable. the data is set up like this: "city" "n" "y" <br> mon 100 200 <br> tor 209 300 <br> edm 98 87 <br> mon 20 76 <br> tor 50 96 <br> edm 62 27 <br> the resulting plot should have city as the x-axis, 2 bars per city, 1 representing

It is not generally advisable to get too fancy with stat functions in ggplot... things can easily get more complicated than ggplot is ready to handle when it comes to calculations. It is better to create data that corresponds directly to the graphical representations you are mapping them to. Read [1] for more on this philosophy. [1] H. Wickham, Tidy Data, Journal of Statistical Software,

On Thu, 26 Oct 2017, Thomas Adams wrote: > Hi Jeff, > > Thank you for the suggestions -- I appreciate your help. Unfortunately, the > result2 has two problems... > > (1) there are now 3 date columns (it looks like 2 cols are merged into 1 > col) No, there are two date columns. Result2 includes the grouping value as a row name (pulled from the names of the dta2list items

Hello all! I've been struggling with is for many hours today; I'm close to getting what I want, but not close enough... I have a dataframe consisting of two date-time columns followed by two numeric columns. what I need is the max value (in the first numeric column) based on the 2nd date-time column, which is essentially a factor. But, I want the result to provide both date-time values

I would like to make a ranking operation more efficient if possible. The goal is to rank a set of points representing objective function values such that points which are "dominated" by no others have rank 1, those which are dominated by one other point have rank 2, etc. In the example with two dimensions below, objective functions 1 and 2 are to be minimized. Points a-e are

Hi Folks, I have just started using dplyr and could use some help getting unstuck. It could well be that dplyr is not the package to be using, but let me just pose the question and seek your advice. Here is my basic data frame. head(h) subject ageGrp ear hearingGrp sex freq L2 Ldp Phidp NF SNR 1 HALAF032 A L A F 2 0 -23.54459 55.56005 -43.08282