R中的dplyr变异-根据另一列的顺序添加新列

Question

I am having an issue with mutate function in dplyr .

• I am trying to add a new column called state depending on the change in one of the column ( V column). (V column repeat itself with a sequence so each sequence (rep(seq(100,2100,100),each=96) corresponds to one dataset in my df )

Error: impossible to replicate vector of size 8064

Here is reproducible example of md df :

df <- data.frame (
    No=(No= rep(seq(0,95,1),times=84)), 
    AC= rep(rep(c(78,110),each=1),times=length(No)/2), 
    AR = rep(rep(c(256,320,384),each=2),times=length(No)/6), 
    AM =  rep(1,times=length(No)),
    DQ = rep(rep(seq(0,15,1),each=6),times=84),
    V = rep(rep(seq(100,2100,100),each=96),times=4),
    R = sort(replicate(6, sample(5000:6000,96))))

labels  <- rep(c("CAP-CAP","CP-CAP","CAP-CP","CP-CP"),each=2016) 

I added here 2016 value intentionally since I know the number of rows of each dataset.

But I want to assign these labels with automated function when the dataset changes. Because there is a possibility the total number of rows may change for each df for my real files. For this question think about its only one txt file and also think about there are plenty of them with different number of rows. But the format is the same.

I use dplyr to arrange my df

library("dplyr")
newdf<-df%>%mutate_each(funs(as.numeric))%>%
mutate(state = labels)

is there elegant way to do this process?

Answer 1

Iff you know the number of data sets contained in df AND the column you're keying off --- here, V --- is ordered in df like it is in your toy data, then this works. It's pretty clunky, and there should be a way to make it even more efficient, but it produced what I take to be the desired result:

# You'll need dplyr for the lead() part
library(dplyr)
# Make a vector with the labels for your subsets of df
labels <- c("AP-AP","P-AP","AP-P","P-P")
# This line a) produces an index that marks the final row of each subset in df
# with a 1 and then b) produces a vector with the row numbers of the 1s
endrows <- which(grepl(1, with(df, ifelse(lead(V) - V < 0, 1, 0))))
# This line uses those row numbers or the differences between them to tell rep()
# how many times to repeat each label
newdf$state <- c(rep(labels[1], endrows[1]), rep(labels[2], endrows[2] - endrows[1]),
    rep(labels[3], endrows[3] - endrows[2]), rep(labels[4], nrow(newdf) - endrows[3]))