similar to: Specifying argument values in a function

Hi, I'm trying to cast() some data, but keep on getting the following error... > norm.all.melted.height <- transform(all.melted.height, + norm.height = value / ave(value, SNP, Pool, FUN = max) + ) Warning messages: 1: In FUN(X[[147L]], ...) : no non-missing arguments to max; returning -Inf 2: In FUN(X[[147L]],

Dear list, I have a data.frame with x, y values and a 3-level factor "group", say. I want to create a new column in this data.frame with the values of y scaled to 1 by group. Perhaps the example below describes it best: > x <- seq(0, 10, len=100) > my.df <- data.frame(x = rep(x, 3), y=c(3*sin(x), 2*cos(x), > cos(2*x)), # note how the y values have a different

Hi @all, I am biting my nails with the following problem: I have a data set of daily rainfall measurements for the last 20 years. What I want to do is calculate the daily cumulative sum of rainfall but only for every year which means that the cumulative sum has to be reset each year. After the calculations I want to plot each year of cumulative rainfall as a separate line in one graph preferably

Hi, I am trying to run a script on R and it died before finish. I already read the list archives, and memory help pages (http://tinyurl.com/yaxco6w), but I am unable to solve the issue. My Debian shows: marcelo at laia:~$ ulimit unlimited marcelo at laia:~$ On system monitor (gnome) I see that R reaches 1.9 Gb, before die. The R code is: > ls() ## only todos.norm object are listed [1]

This is my first excursion into using reshape2 and I want to ensure that the melt() function call is syntactically correct. The unmodifed data frame is organized this way: head(tds.anal) site sampdate param quant 1 UDS-O 2006-12-06 TDS 10800 4 STC-FS 1996-06-14 Cond 280 7 UDS-O 2007-10-04 Mg 1620 9 UDS-O 2007-10-04 SO4 7580 19 JCM-10B 2007-06-21 Ca 79 20

Hola Soy Leticia, quería hacer una consulta al grupo a ver si me podéis ayudar. Tengo unos datos de proteínas, el data frame es: 5 columnas iniciales que tienen información sobre las proteínas y después las columnas con las intensidades, de las cuales no se cuantas condiciones tienen ni cuántas réplicas por condición. Estoy intentando hacer un cálculo del coeficiente de variación por grupo y

Hi, I misunderstand the definition of Canberra distance in R. On Internet and in function description pages of dist() from stats and Dist() from amap, Canberra distance between vectors x and y, d(x,y), is : d(x,y) = sum(abs(x-y)/(x+y)) But in use, through simple examples, we find that the formula is : d(x,y) = (NZ + 1)/NZ * sum(abs(x-y)/(x+y)) with NZ = nb of pairs of coordinates that are

I start with a dataframe called xrays. It contains scores on films from each of two radiologists. It is in "long" format. I used the reshape package to melt a data frame and then cast it into "wide" format, one line for each patient (identified by redlognumb) with scores from both radiologists for a given patient on the same line. I named the result of the casting xrays.data.

Hola Leticia Acomodar datos para analizar suele llevar más trabajo que el análisis. Yo prefiero en un data.frame colocar todos los datos, porque siempre es más fácil filtrar que agregar. Cuándo tengo el data.frame con todo, realizo un plot (datos), y muchas veces en la gráfica veo cosas que me llaman la atención, de esta forma busco algo de antemano no sospechaba. No es necesario que conozcas

Hola a todos! Soy nueva en R y necesito hacer unos gráficos para una investigación, he explorado un poco y estoy intentando usar ggplot2 ya que hace gráficos de muy buena calidad...tengo los datos de varios años para diferentes grupos de empresas y los pretendo graficar tanto en un solo grafico como en varios (facet_wrap) pero tengo problemas con el eje de las X, ya que necesito que aparezcan los

Muchas fracias por la rapida contastacion Javier. Si, ya me he dado cuenta que a veces es mas limpiar y formatear que calcular. Lo que yo necesito hacer no es crear un data.frame, es crear una lista por cada grupo/condicion de muestras. Y queria hacerlo en un for loop, para que no tuviese que indicar cuantas listas necesito si no que cogiese esa informacion del usuario (y) Creo que no me

Hola, que tal? Sin saber nada mas de los datos, por lo que dices, mi aprioximacion seria usar la funcion split, e.g.: splittedData <- split(myData, "variablegrupo/condicion") Esto te crearia una lista con tantos objectos como condiciones tengas. Saludos On 6/27/24 10:15, Leticia G Leon wrote: > Muchas fracias por la rapida contastacion Javier. > > Si, ya me he dado

Hello everyone! My data is composed of 277 individuals measured on 8 binary variables (1=yes, 2=no). I did two similar cluster analyses, one on SPSS 18.0 and one on R 2.9.2. The objective is to have the means for each variable per retained cluster. 1) the R analysis ran as followed: > call data > dist=dist(data,method="euclidean") >

Using the small reproducible example below, I'd like to know if one can somehow use the matrix "sig" (defined below) to add a black outline (with lwd=2) to all pixels with a corresponding value of 1 in the matrix 'sig'? So for example, in the ggplot2 plot below, the pixel located at [1,3] would be outlined by a black square since the value at sig[1,3] == 1. This is my first

Dear, I have a data frame melted from a list of matrices (melt from reshape package), then I impute some missing values and then want to tabulate the data again to the array (or list, doesn't matter) of matrices form. However when using xtabs function it orders my rows alphabetically and apparently doesn't take "reorder = FALSE" option or anything like it. Is there anything I

Dear R-users, I want to perform a One-Sample parametric bootstrapped Kolmogorov-Smirnov GoF test (note package "Matching" provides "ks.boot" which is a 2-sample non-parametric bootstrapped K-S version). So I wrote this code: ---[R Code] --- ks.test.bootnp <- function( x, dist, ..., alternative=c("two.sided", "less", "greater"), B = 1000 ) {

I am new to R and have two scripts written slightly different but should to relatively the same thing but my lack of experience with the program I can not figure out the what I need to do to correct it. The first script gives me a consistent mean fold change values with every run but can generate negative p values for some. For the second version of the script, the fold changes seem to be very

Dear R-experts, this is not a direct R-problem but I hope you can help me anyway. I would like to minimize || PG-I || over P, where P is a p x p permutation matrix (obtained by permuting the rows and/or columns of the identity matrix), G is a given p x p matrix with full rank and I the identity matrix. ||.|| is the frobenius norm. Does anyone know an algorithm to solve such a problem? And if

Hi, I'm trying to melt() some data for subsequent cast()ing and am encoutering errors. The overall process requires a couple of casts()s and melt()s. ########Start Session 1########## ## I have the data in a (fully) melted format and can cast it fine... > norm1[1:10,] Pool SNP Sample.Name variable value 1 1 rs1045485 CA0092 Height.1 0.003488853 2 1 rs1045485

Hello, I have a ggplot that has the looks of the plot that I want, but it doesn't have the right layout. The data is an ordered melted dataframe: - ID - type (to use for a faced grid) - time - type - time - value (POSIXct) - pos (to use for a faced grid, this is an index to split the plot) The goal of the plot is to create a time line for each ID (different points of time). The ID's