search for: new_df

...ot;, "Q", "S", "L", "T", "U", "V", "W", "X", "Y", "Z", "CC", "AA", "BB", "Y") ref_df <- data.frame (ID, Year, new_ID) ref_df rep_val <- rep(0, nrow(df)) new_df <- data.frame(ID=rep_val, Year=rep_val, newID=rep_val, hmyears=rep_val) for(i in 1:nrow(df)) { #Cero print(i) if(i==1) { new_df$ID[i] <- df$ID[i] new_df$Year[i] <- df$Year[i] new_df$newID[i] <- df$ID[i] new_df$hmyears[i] <- 1 } else {...

...N", "Q", "S", "L", "T", "U", "V", "W", "X", "Y", "Z", "CC", "AA", "BB", "Y")ref_df <- data.frame (ID, Year, new_ID)ref_df rep_val <- rep(0, nrow(df))new_df <- data.frame(ID=rep_val, Year=rep_val, newID=rep_val, hmyears=rep_val )for(i in 1:nrow(df)) { #Cero if(i==1) { new_df$ID[i] <- df$ID[i] new_df$Year[i] <- df$Year[i] new_df$newID[i] <- df$ID[i] new_df$hmyears[i] <- 1 } else { #Uno coin...

...ue momento fue capturado cada individuo y por tanto si es posible o no que el individuo sea el mismo a lo largo del tiempo. newID <-sapply(unique(database$ID_original), function(x) c(0,cumsum(diff(database$Month_Capt[database$ID_original==x]))%%48))names(newID)<-(unique(database$ID_original)) new_df<-data.frame(database$ID_original,database$Month_Capt,IDcond=NA,new_ID=NA)for(i in unique(database$ID_original)){ new_df[new_df[,1]==i,3]<-newID[[which(unique(database$ID_original)==i)]]}ltrs<-c(LETTERS,apply(combn(LETTERS,2,simplify = T),2,function(x) paste(x,sep = "",collapse =...

Hi, I have a data frame with 100 variables (numeric and non numeric types), and I want to join them in only one column, like a vector, but i want to keep the non numeric variables like they are. I know that i can do something like this: Suppose that my data is in df variable new_df<-data.frame(c(df[,1],df[,2],df[,3],df[,4],...........) This works but i have 100 variables! Any way of doing this a little bit faster? Thanks a lot! -- View this message in context: http://r.789695.n4.nabble.com/Join-data-frame-columns-tp4647113.html Sent from the R help mailing list arc...

...ons terms (after the first undefined coefficient) from a:a, c:a, g:a, ... to a:1, c:1, g:1, ... and obviously omits direct calculation of interaction terms of the form a:4, c:4, g:4, t:4 which (if I correctly assume) correspond to a:t, c:t, g:t, t:t. 2.) How I have to correctly define a data frame new_df for a new sequence of letters to get the predicted response by using the predict function, I tried something like this: >new_df[2:5]=as.data.frame(t('g')) >new_df[1]=0 >predict(lm, new_df) and also the original data frame which was used to fit the model: >predict(lm, df[1,])...

...ons terms (after the first undefined coefficient) from a:a, c:a, g:a, ... to a:1, c:1, g:1, ... and obviously omits direct calculation of interaction terms of the form a:4, c:4, g:4, t:4 which (if I correctly assume) correspond to a:t, c:t, g:t, t:t. 2.) How I have to correctly define a data frame new_df for a new sequence of letters to get the predicted response by using the predict function, I tried something like this: >new_df[2:5]=as.data.frame(t('g')) >new_df[1]=0 >predict(lm, new_df) and also the original data frame which was used to fit the model: >predict(lm, df[1,])...

...like this: Year of Record Sales Region Target Brand 3M Avery Here is what I did. 1. I split the original data frame which I called data1: X = split(data1, Product_name) 2. Unlist X X1 = unlist(X) 3. Create a new data frame new_df = as.data.frame(X1) But, when I used the command View(new_df), I had only two columns: The left one is similar to TargetBrand.Sales, etc. and the right one is just "X1" I did not achieve what I wanted. **A potentially big question from readers:* Why am I doing this? *Answer:* I wan...

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”,...

...output by the VOStat GUI. I have ways to format the output using Java by displaying it in a tabular form with grid lines. But I am facing problems in doing so when the R output is truncated to a new line, for instance when the number of columns is large. A trivial example is mentioned below:- new_df<- data.frame("League Position"=1, "Team"="Manchester City", "Games played"=38, "Games won"=28, "Games drawn"=5, "Games lost"=5, "Goals scored"=93, "Goals conceded"=29, "Goal difference"=64, "...

...like this: ? ? ? ? ? ? ? ? ? ? ? Year of Record? ? ? ?Sales? ? ?Region ? Target Brand ? 3M ? Avery Here is what I did. ? ?1. ? ?I split the original data frame which I called data1: ? ?X = split(data1, Product_name) ? ?2. ? ?Unlist X ? ?X1 = unlist(X) ? ?3. ? ?Create a new data frame ? ?new_df = as.data.frame(X1) But, when I used the command View(new_df), I had only two columns: The left one is similar to TargetBrand.Sales, etc. and the right one is just "X1" I did not achieve what I wanted. **A potentially big question from readers:* Why am I doing this? *Answer:* I wan...

...like this: ? ? ? ? ? ? ? ? ? ? ? Year of Record? ? ? ?Sales? ? ?Region ? Target Brand ? 3M ? Avery Here is what I did. ? ?1. ? ?I split the original data frame which I called data1: ? ?X = split(data1, Product_name) ? ?2. ? ?Unlist X ? ?X1 = unlist(X) ? ?3. ? ?Create a new data frame ? ?new_df = as.data.frame(X1) But, when I used the command View(new_df), I had only two columns: The left one is similar to TargetBrand.Sales, etc. and the right one is just "X1" I did not achieve what I wanted. **A potentially big question from readers:* Why am I doing this? *Answer:* I wan...

If no one has a better solution, split it, take a sample of size X from both and put it back together. hgwelec wrote: > > Dear members, > > Consider the following data frame (first 4 rows shown) > > > age sex class > 15 m low > 20 f high > 15 f low > 10 m low > > in my original data set i have 1200 rows and a class distribution

...oseph <jdsandjd at yahoo.com> Subject: [R] data frame question To: r-help at r-project.org Cc: r-help at r-project.org Message-ID: <109232.80965.qm at web36905.mail.mud.yahoo.com> Content-Type: text/plain 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?,...