similar to: Remove rows with NA across all columns

Hello I have 2 data frames df1 and df2. I would like to create a new data frame new_df which will contain only the common rows based on the first 2 columns (chrN and start). The column score in the new data frame should be replaced with a column containing the average score (average_score) from df1 and df2. df1= data.frame(chrN= c(“chr1”, “chr1”, “chr1”, “chr1”, “chr2”, “chr2”, “chr2”),

Hi, I'm looking for some lines of code that does the following: I have a dataframe with 160 Columns and a number of rows (max 30): Col1 Col2 Col3 ... Col 159 Col 160 Row 1 0 0 LD ... 0 VD Row 2 HD 0 0 0 MD Row 3 0 HD HD 0 LD Row 4 LD HD HD 0 LD ... ... LastRow HD HD LD 0 MD Now I want a dataframe that looks like this. As you see

Hi: Can anyone advice me on how to loop and perform a calculation through all the columns. here's my data xd<- c(2.2024,2.4216,1.4672,1.4817,1.4957,1.4431,1.5676) pd<- c(0.017046,0.018504,0.012157,0.012253,0.012348,0.011997,0.012825) td<- c(160524,163565,143973,111956,89677,95269,81558) mydf<-data.frame(xd,pd,td) trans<-t(mydf) trans I have these values that I need to

Hi, I am a little new in R but I'm finding it extremely useful :) Here's my tiny question: I've got a table with a lot of columns. What I am interested now is to evaluate how many of 4 columns have a value greater than 1. I think it can be done with subset() but it will take a very long condition and become unfeasible if I want to compare more than 4 columns. I put here a small

I had an NA in one row of my data frame, so I called na.omit(). But I do not understand where that row disappeared to. >fri=na.omit(fri) > fri Date.Only DAY Hour Min15 Quarter Arrival.Val Arrival4 1 09/05/2008 Friday 8 33 3 32 8 2 10/24/2008 Friday 21 86 4 28 7 3 10/31/2008 Friday 8 33 4 20

Dear R users, I??ve got a simple question but somehow I can??t find the solution: I have a data frame with columns 1-5 containing one set of integer values, and columns 6-10 containing another set of integer values. Columns 6-10 contain NA??s at some places. I now want to calculate (1) the number of values in each row of columns 6-10 that were NA??s (2) the sum of all values on columns 1-5

Hi, I have the following data frame, where col2 is a startdate and col3 an enddate COL1 COL2 COL3 A 40462 40482 B 40462 40478 The above timeframe of 3 weeks I would like to splits it in weeks like this COL1 COL2 COL3 COL4 A 40462 40468 1 A 40469 40475 1 A 40476 40482 1 B

Suppose I have the following sort of dataframe, where each column name has a common structure: prefix, followed by a number (for this example, col1, col2, col3 and col4): d = data.frame( col1=runif(10), col2=runif(10), col3=runif(10),col4=runif(10)) What I haven't been able to suss out is how to efficiently 'extract/manipulate/play with' columns from the data frame, making use

Hi all, I put up an exhaustive model to use R's "step" function: ------------------------ mygam=gam(col1 ~ 1 + col2 + col3 + col4 + col2 ^ 2 + col3 ^ 2 + col4 ^ 2 + col2 ^ 3 + col3 ^ 3 + col4 ^ 3 + s(col2, 1) + s(col3, 1) + s(col4, 1) + s(col2, 2) + s(col3, 2) + s(col4, 2) + s(col2, 3) + s(col3, 3) + s(col4, 3) + s(col2, 4) + s(col3, 4) + s(col4, 4) + s(col2, 5) + s(col3,

Thank you Jim, I read the data as you suggested but I could not find K1 in col1. rbind(preval,mydat) Col1 Col2 col3 1 <NA> <NA> <NA> 2 X1 <NA> <NA> 3 Y1 <NA> <NA> 4 K2 <NA> <NA> 5 W1 <NA> <NA> 6 Z1 K1 K2 7 Z2 <NA> <NA> 8 Z3 X1 <NA> 9 Z4 Y1 W1 On Sat, Feb 24, 2018 at 6:18 PM, Jim

Hi Val, My fault - I assumed that the NA would be first in the result produced by "unique": mydat <- read.table(textConnection("Col1 Col2 col3 Z1 K1 K2 Z2 NA NA Z3 X1 NA Z4 Y1 W1"),header = TRUE,stringsAsFactors=FALSE) val23<-unique(unlist(mydat[,c("Col2","col3")])) napos<-which(is.na(val23)) preval<-data.frame(Col1=val23[-napos],

HI Jim and all, I want to put one more condition. Include col2 and col3 if they are not in col1. Here is the data mydat <- read.table(textConnection("Col1 Col2 col3 K2 X1 NA Z1 K1 K2 Z2 NA NA Z3 X1 NA Z4 Y1 W1"),header = TRUE,stringsAsFactors=FALSE) The desired out put would be Col1 Col2 col3 1 X1 0 0 2 K1 0 0 3 Y1 0 0 4 W1 0 0 6 K2 X1

I am finding complex analyses easier than some elementary operations in R. In particular I want to do some low level exploratory data analyses with data in a data frame but cannot find commands to easily insert, remove (delete), rename, and re-order (arbitrarily, not sort) columns. I see that the micEcon package has an insertCol command, but that is for matrices, not data frames. I have looked

Sorry , I hit the send key accidentally here is my complete message. Thank you Jim and all, I got it. I have one more question on the original question What does this "[-1] " do? preval<-data.frame(Col1=unique(unlist(mydat[,c("Col2","col3")]))[-1], Col2=NA,col3=NA) mydat <- read.table(textConnection("Col1 Col2 col3 Z1 K1 K2 Z2

Hi, I cannot figure out how to draw a certain plot: could someone help me out? I have this data.frame from a survey my.data that looks like something like this: col1 col2 col3 col4 1 5 5 4 5 2 3 5 3 1 3 2 3 4 5 4 3 1 1 2 5 5 5 4 5 6 4 2 5 5 .... Each row represents a single questionnaire

Hi, I would like to split dataframe based on one colum and want to connect the two dataframes by rows (like rbind). Here a small example: # The orgininal dataframe df1 <- data.frame(col1 = c("A","A","B","B"),col2 = c(1:4), col3 = c(1:4)) # The datafame how it could look like df2 <- data.frame(A.col2 = c(1,2), A.col3 = c(1,2), B.col2 = c(3,4), B.col3

Dear R Community, The following seems like a simple problem, but I''ve been stuck on it for some time, with no luck using matching or subsetting functions. I''m trying to remove the rows from a large matrix that match rows in another large matrix. A (small scale) example: col1<-c("A", "B", "C", "D") col2<-c("A",

Jim has been exceedingly patient (and may well continue to be so), but this smells like "failure to launch". At what point will you start showing your (failed) attempts at solving your own problems so we can help you work on your specific weaknesses and become self-sufficient? -- Sent from my phone. Please excuse my brevity. On February 25, 2018 7:55:55 AM PST, Val <valkremk at

hi Val, Your problem seems to be that the data are read in as a factor. The simplest way I can think of to get around this is: mydat <- read.table(textConnection("Col1 Col2 col3 Z1 K1 K2 Z2 NA NA Z3 X1 NA Z4 Y1 W1"),header = TRUE,stringsAsFactors=FALSE) preval<-data.frame(Col1=unique(unlist(mydat[,c("Col2","col3")]))[-1], Col2=NA,col3=NA) rbind(preval,mydat)

> On Jun 21, 2017, at 9:11 AM, Evan Cooch <evan.cooch at gmail.com> wrote: > > Suppose I have the following sort of dataframe, where each column name has a common structure: prefix, followed by a number (for this example, col1, col2, col3 and col4): > > d = data.frame( col1=runif(10), col2=runif(10), col3=runif(10),col4=runif(10)) > > What I haven't been able to