similar to: Making multiple columns to a single column

Hi guys, I need your help. I'm trying to sort the data by the variable "obs". This is how I tried to sort the data below. The problem is, I have a variable name "obs"; this is.. a counter variable. something like _n_ in SAS. I do not know why it is not working. I even tried a similar example in UCLA webpage: http://www.ats.ucla.edu/stat/R/faq/sort.htm :it also does not

Hi guys, I need your help!! My goal is to make a csv file from ncdf file. This is the code i've used : > hyo=open.ncdf("C:/CRUTEM3.nc") > hyo [1] "file C:/CRUTEM3.nc has 4 dimensions:" [1] "longitude Size: 72" [1] "latitude Size: 36" [1] "unspecified Size: 1" [1] "t Size: 1916" [1] "------------------------"

I''m to porting a lightweight kernel to Xen 3.0.4-x86_64 and have run into a problem while setting the PML4. Xen complains that it has a bad type of ''PGT_writable_page'' (e8000001), while it expects 80000000. However, I''m almost certain that this is not the case. I added a routine to do a depth first search of the four page table levels looking for this machine

Hi I have a plist t which contains size measurements of individual plants, identified by the field "plate". It contains, among other, a field "year" indicating the year in which the individual was measured and the "height". The number of measurements range from 1 to 4 measurements in different years. My problem is that I would need the LAST measurement. I only

I have a repetative task in R and i'm trying to find a more efficient way to perform the following task. lst <- list(roots = c("car insurance", "auto insurance"), roots2 = c("insurance"), prefix = c("cheap", "budget"), prefix2 = c("low cost"), suffix = c("quote", "quotes"),

I am experiencing some problems at working with lists at high level. In the following "coef" contains the original DWT coefficients organized in a list. Thorugh applying the following two commands: coef.abs <- lapply(unlist(coef,recursive=FALSE,use.names =TRUE),abs) coef.abs.sorted <- sort(unlist(coef.abs),decreasing=TRUE) I get vector "coef.abs.sorted" containing

Hi, I have one critical question in using R. I am currently working on some research which involves huge amounts of data(it is about 15GB). I am trying to use R in this research rather than using SAS or STATA. (The company where I am working right now, is trying to switch SAS/STATA to R) As far as I know, the memory limit in R is 4GB; However, I believe that there are ways to handle the large

Dear R-list members, I've had a hard time trying to solve a non-linear system (nls) of equations which structure for the equation i, i=1,...,4, is as follows: f_i(d_1,d_2,d_3,d_4)-k_i(l,m,s) = 0 (1) In the expression above, both f_i and k_i are known functions and l, m and s are known constants. I would like to estimate the vector d=(d_1,d_2,d_3,d_4) which is solution

For learning purposes mainly I attempted to implement hashes/maps/dictionaries (Python lingua) as S4 classes, see the coding below. I came across some rough S4 edges, but in the end it worked (for one dictionary). When testing ones sees that the dictionaries D1 and D2 share their environments D1 at hash and D2 at hash, though I thought a new and empty environment would be generated each time

Hello R-Community, I have the following matching problem: I have two data.frames, one with an observation every month (per company ID), and one with an observation every quarter (per company ID; note that quarter means fiscal quarter; therefore 1Q = Jan, Feb, Mar is not necessarily correct and also, a fiscal quarter is not necessarily 3 month long). For every month and company, I want to get the

For certain reason, the content was not visible in the last mail, so posting it again. Dear Members, I have two different dataframes with a different number of rows. I need to apply a set of functions to each possible combination of rows with one row coming from 1st dataframe and other from 2nd dataframe. Though I am able to perform this task using for loops, I feel that there must be a more

I'm trying to do the following: For each ordered pair of a data frame (D1) containing longitudes and latitudes and unique point IDs, calculate the distance to every point in another data frame (D2) also containing longitudes, latitudes and point IDs, and return to a new variable in D1 the point ID of the nearest element of D2. Dramatis personae (mostly self-explanatory): D1$long

Estimados Cuando existia epicalc, había una manera muy fácil de determinar la media de una variable (en esta caso Gain) por grupos, en este caso (Diet). ?Como se puede hacer ahora? Diet Gain 1 d1 270 2 d1 300 3 d1 280 4 d1 280 5 d1 270 6 d2 290 7 d2 250 8 d2 280 9 d2 290 10 d2 280 11 d3 290 12 d3 340 13 d3 330 14 d3 300 15 d3 300

I wonder if there is a more efficient way to do this task. Suppose I have two data frames, such as d1 <- data.frame(x = c(1,2,3), y = c(4,5,6), z = c(7,8,9)) d2 <- d1[, c('y', 'x')] The first dataframe d1 has more variables than d2 and the variable columns are in a different order. So, what I want to do is compare the two frames on the variables that are common between

I have two CSV files (exported from Excel), say file1 and file2. The have the same number of rows, and each has several columns, with names on the first line; and some of the columns in file1 are repeated in file2. Using the "foreign" package, I can read these in separately to dataframes say d1 and d2 with > d1<-read.csv("file1") >

Hi, I have 2 date vectors d1 and d2. d1 <- structure(c(14526, 14495, 14464, 14433, 14402, 14371, 14340, 14309, 14278, 14247, 14216, 14185), class = "Date") d2 <- structure(c(14526, 14509, 14488, 14466, 14453, 14441, 14396, 14388, 14343, 14333, 14310, 14281), class = "Date") I would like to create another dataframe with columns d1 and d2, where d1 is the original d1

Hi, I would like to merge two data frames. It is just that I want the merging to be done with some kind of a fuzzy criterion. Let me explain. My first data frame looks like this : ID1 time1 dt 1 2008-01-02 13:11 10 2 2008-01-02 14:20 20 3

Hi: I am a new R user. I have the following question and would appreciate your input Data1 (data frame 1) p1,d1,d2 (p1 is text and d1 and d2 are numeric) xyz,10,25 Data2 (data frame 2) p1,d1,d2 xyz,11,15 Now I want to create a new data frame that looks like so below. The fields d1 and s2 are summed by the product key. Data3 p1,d1,d2 xyz,21 (sum of 10 from Data1 and 11 from Data2),40 (sum of 25

Hi, I would like to find out the coordinates of the intersection points of 2 density curves. I did a search but i didn't get any significant results. I really hope some of you have some ideas. here it is an example: set.seed(123) x1 <- rnorm(100, 1, 1) x2 <- rnorm(100, 0, 1) d1 <- density(x1) d2 <- density(x2) plot(d1, col = 2) lines(d2, col = 4) Now i would like to know

The following series adds initial vector support for PowerPC64. On POWER9, flac --best is about 3.3x faster. Amitay Isaacs (2): Add m4 macro to check for C __attribute__ features Check if compiler supports target attribute on ppc64 Anton Blanchard (5): configure.ac: Remove SPE detection code configure.ac: Add VSX enable/disable configure.ac: Fix FLAC__CPU_PPC on little endian, and add