I am working with a big dataset that is causing some trouble because some of the columns I the dataset are being treated as factors. How can I convert all of the columns from factor to numeric, without having to do that column by column??
I have tried to apply a small loop, but it returns NA values. Here's a sample data that applies to the case:
data <- structure(list(v1 = c(22.394, 43.72, 58.544, 56.877, 1.659, 29.142,
67.836, 68.851), v2 = c(144.373, 72.3, 119.418, 112.429, 35.779,
41.661, 166.941, 126.548), v3 = structure(c(33L, 29L, 33L, 5L,
13L, 31L, 5L, 8L), .Label = c("", "#VALUE!", "0", "1", "10",
"11", "12", "13", "14", "15", "16", "17", "18", "19", "2", "20",
"21", "22", "23", "24", "25", "26", "28", "29", "3", "30", "32",
"33", "4", "48", "5", "6", "7", "8", "9"), class = "factor"),
v4 = structure(c(24L, 6L, 22L, 23L, 16L, 22L, 23L, 26L), .Label = c("",
"-1", "-2", "-4", "#VALUE!", "0", "1", "10", "11", "12",
"13", "14", "15", "16", "17", "18", "19", "2", "24", "28",
"29", "3", "4", "5", "6", "7", "8", "9"), class = "factor")), .Names = c("v1",
"v2", "v3", "v4"), row.names = c("4", "5", "6", "7", "8", "9",
"10", "11"), class = "data.frame")
for (i in 1:ncol(data)){
data[,i] <- as.numeric(as.character(data[i]))
} ## returns NAs
Is there some command that I can apply to turn all these columns into a numeric class?
This works but I'm thinking your data has an odd character or space, something that makes it read in as factor. You can try reading in with the argument stringsAsFactors = FALSE. But still wouldn't address character vs numeric read in. Here's a fix:
data[] <- lapply(data, function(x) as.numeric(as.character(x)))
## > str(data)
## 'data.frame': 8 obs. of 4 variables:
## $ v1: num 22.39 43.72 58.54 56.88 1.66 ...
## $ v2: num 144.4 72.3 119.4 112.4 35.8 ...
## $ v3: num 7 4 7 10 18 5 10 13
## $ v4: num 5 0 3 4 18 3 4 7