How can I replace hyphen "cells" in R data frames with zeros? - r

Question

I have a data frame with some positive numbers, some negative numbers, some words, and some hyphen "cells" in it, as such:
Revenue 73.88 74.76 78.02 78.19 68.74
Other Revenue - Total - - - - -
Total Revenue 73.88 74.76 78.02 78.19 68.74
Cost of Revenue - Total 21.09 21.61 23.01 22.76 19.99
Gross Profit 52.80 -53.15 -55.01 55.43 48.75
I want to replace the hyphens that are only found in the second to last columns with 0s, but only if the hyphens are not at the beginning of numbers. For example, I don't want to turn a negative number positive.
I've tried:
df[-1] <- lapply(df[-1], function(x) as.numeric(gsub("-", 0, x)))
but that returns the previous data frame as:
Revenue NA NA NA NA NA
Other Revenue - Total 0 0 0 0 0
Total Revenue NA NA NA NA NA
Cost of Revenue - Total NA NA NA NA NA
Gross Profit NA NA NA NA NA
which is something I definitely don't want. How can I fix this?
Thanks.
This is the output when I call str():
str(income)
'data.frame': 49 obs. of 6 variables:
$ Items : Factor w/ 49 levels "Accounting Change",..: 44 40 47 7 23 45 43 9 29 49 ...
$ Recent1: Factor w/ 14 levels "-","0.00","11,305.00",..: 4 1 4 11 14 6 5 1 1 1 ...
$ Recent2: Factor w/ 16 levels "-","-29.00","0.00",..: 5 1 5 15 16 9 6 1 1 2 ...
$ Recent3: Factor w/ 17 levels "-","0.00","11,449.00",..: 5 1 5 15 17 10 6 1 1 4 ...
$ Recent4: Factor w/ 18 levels "-","-31.00","0.00",..: 6 1 6 15 17 9 4 1 1 18 ...
$ Recent5: Factor w/ 14 levels "-","0.00","1,617.00",..: 4 1 4 10 13 5 3 1 1 1 ...

Answer 1

As #Joe hinted at, the values in a column of a data.frame have to be of the same type, so given that you have -s in the same vectors as what appear to be numerics (52.80, 21.09, etc...), each column is being forced to type character (presumably). Try gsubbing with "0" instead of 0 and then converting the columns to numeric. Since you are forcing a 0 into a character column vector, it is coercing the rest of the vector elements to NA.
DF <- data.frame(
X1=c(12,45,67,"-",9),
X2=c(34,45,56,"-",12))
str(DF)
'data.frame': 5 obs. of 2 variables:
$ X1: chr "12" "45" "67" "-" ...
$ X2: chr "34" "45" "56" "-" ...
##
DF2 <- DF
DF2$X1 <- gsub("-","0",DF2$X1)
DF2$X1 <- as.numeric(DF2$X1)
str(DF2)
'data.frame': 5 obs. of 2 variables:
$ X1: num 12 45 67 0 9
$ X2: chr "34" "45" "56" "-" ...
EDIT: To remove the commas in your values,
DF <- data.frame(
X0=c("A","B","C","D"),
X1=c("12,300.04","45.5","-","9,046.78"),
X2=c("1,0001.12","33","-","12.6"))
for(j in 2:ncol(DF)){
DF[,j] <- gsub(",","",as.character(DF[,j]))
for(i in 1:nrow(DF)){
if(nchar(DF[i,j])==1){
DF[i,j] <- gsub("-","0",DF[i,j])
} else {
next
}
}
DF[,j] <- as.numeric(DF[,j])
DF[,j]
}
There are more efficient ways of doing this with *apply functions and regular expressions but this should work. I had to account for the fact that some of your values are negative so assuming the cells with only a - in them are only one character long, this should fix them without affecting the negative values in other cells.

Answer 2

Assume it is named dat:
dat[2:6] <- lapply( dat[2:6], function(col) as.numeric( gsub("-$|\\,", "", col) ) )
dat[is.na(dat)] <- 0
Only replaces minus-signs at the end of a string, removes commas and the gsub coerces factors to character so you don't need to add as.character. When I imported your data using read.fwf and textConnection I got trailing spaces. You can either use gdata::trim to remove those first but this worked:
lapply(dat[2:6], function(col) as.numeric( gsub("-[ ]*$|\\,", "", col ) ) ) # on RHS
dat<-read.fwf(textConnection("Revenue 73.88 74.76 78.02 78.19 68.74
Other Revenue - Total - - - - -
Total Revenue 73.88 74.76 78.02 78.19 68.74
Cost of Revenue - Total 21.09 21.61 23.01 22.76 19.99
Gross Profit 52.80 -53.15 -55.01 55.43 48.75"), widths=c(24, rep(8,5)))
dat[2:6] <- lapply( dat[2:6], function(col) as.numeric( gsub("-$|\\,", "", col) ) )
dat[is.na(dat)] <- 0
dat
#----------
V1 V2 V3 V4 V5 V6
1 Revenue 73.88 74.76 78.02 78.19 68.74
2 Other Revenue - Total 0.00 0.00 0.00 0.00 0.00
3 Total Revenue 73.88 74.76 78.02 78.19 68.74
4 Cost of Revenue - Total 21.09 21.61 23.01 22.76 19.99
5 Gross Profit 52.80 -53.15 -55.01 55.43 48.75