R的所有列从因子更改为数字
问题说明
我正在处理一个大数据集，该数据集引起了一些麻烦，因为数据集中的某些列被视为因素.如何将所有列从因子转换为数字，而不必逐列执行?
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??
我尝试应用一个小循环，但它返回 NA 值.以下是适用于该案例的示例数据:
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
我可以应用一些命令将所有这些列转换为数字类吗?
Is there some command that I can apply to turn all these columns into a numeric class?
正确答案
这行得通，但我认为您的数据有一个奇怪的字符或空格，这使它成为读取的因素.您可以尝试使用参数 stringsAsFactors = FALSE 进行读取.但仍然无法解决字符与数字读入的问题.这是一个修复:
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
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