问题
I have a large data-frame (approx 1,000 rows and 30,000 columns) that looks like this:
chr pos sample1 sample2 sample3 sample 4
1 5050 1 NA 0 0.5
1 6300 1 0 0.5 1
1 7825 1 0 0.5 1
1 8200 0.5 0.5 0 1
where at a given "chr"&"pos" the value for a given sample can take the form of 0, 0.5, 1, or NA. I have a large number of queries to perform that will require subsetting and ordering the data frame based on summaries of the values for each sample.
I would like to get a count of the number of occurrences of a given value (e.g. 0.5) for each column, and save that as a new row in my data frame. My ultimate goal is to be able to use the values of the new row to subset and/or order the columns of my data frame. I've seen similar questions about counting occurrences, but I can't seem to find/recognize a solution to doing this across all columns simultaneously and saving the column-wise counts for a particular value as a new row.
回答1:
you can apply a function to all the column of you data.frame. Suppose you want to count the number of 'A' in each column of the data.frame d
#a sample data.frame
L3 <- LETTERS[1:3]
(d <- data.frame(cbind(x = 1, y = 1:10), fac = sample(L3, 10, replace = TRUE)))
# the function you are looking for
apply(X=d,2,FUN=function(x) length(which(x=='A')))
回答2:
Very similar to @Jilber. Assumes your data is in a data frame df
.
lst <- colnames(df[,-(1:2)])
count.na <- sapply(lst,FUN=function(x,df){sum(is.na(df[,x]))},df)
count.00 <- sapply(lst,FUN=function(x,df){sum(df[,x]==0,na.rm=T)},df)
count.05 <- sapply(lst,FUN=function(x,df){sum(df[,x]==0.5,na.rm=T)},df)
count.10 <- sapply(lst,FUN=function(x,df){sum(df[,x]==1.0,na.rm=T)},df)
df <- rbind(df,
c(NA,NA,count.na),
c(NA,NA,count.00),
c(NA,NA,count.05),
c(NA,NA,count.10))
You would probably want to replace the NA's in the last rbind(...) statement with something that identifies what you are counting.
来源:https://stackoverflow.com/questions/20305851/r-how-to-count-occurrences-of-values-across-multiple-columns-of-a-data-frame-and