How to combine multiple variable data to a single variable data? - r

Question

After making my data frame, and selecting the variables i want to look at, i face a dilemma. The excel sheet which acts as my data source was used by different people recording the same type of data.
Mock Neg Neg1PCR Neg2PCR NegPBS red Red RedWine water Water white White
1 9 1 1 1 2 18 4 4 4 2 26
As you can see, because the data is written diffently, Major groups (Redwine, Whitewine and Water) have now been split into undergroups . How do i combine the undergroups into a combined group eg. red+Red+RedWine -> Total wine. I use the phyloseq package for this kind of dataset

Answer 1

names <- c("red","white","water")
df2 <- setNames(data.frame(matrix(ncol = length(names), nrow = nrow(df))),names)
for(col in names){
df2[,col] <- rowSums(df[,grep(col,tolower(names(df)))])
}
here
grep(col,tolower(names(df)))
looks for all the column names that contain the strings like "red" in the names of your vector. You then just sum them in a new data.frame df2 defined with the good lengths

Answer 2

I would just create a new data.frame, easiest to do with dplyr but also doable with base R:
with dplyr
newFrame <- oldFrame %>% mutate(Mock = Mock, Neg = Neg + Neg1PCR + Neg2PCR + NegPBS, Red = red + Red + RedWine, Water = water + Water, White = white = White)
with base R (not complete but you get the point)
newFrame <- data.frame(Red = oldFrame$Red + oldFrame$red + oldFrame$RedWine...)

Answer 3

One can use dplyr:starts_with and dplyr::select to combine columns. The ignore.case is by default TRUE in dplyr:starts_with with help in the data.frame OP has posted.
library(dplyr)
names <- c("red", "white", "water")
cbind(df[1], t(mapply(function(x)rowSums(select(df, starts_with(x))), names)))
# Mock red white water
# 1 1 24 28 8
Data:
df <- read.table(text =
"Mock Neg Neg1PCR Neg2PCR NegPBS red Red RedWine water Water white White
1 9 1 1 1 2 18 4 4 4 2 26",
header = TRUE, stringsAsFactors = FALSE)