这是这个情节的答案:
dat <- read.csv('Rates.csv', stringsAsFactors = FALSE, skip = 19)
colnames(dat)[which(names(dat) %in% c("y", "y.1", "y.2", "y.3"))] <- c("Age", "Revenge", "Homicide", "Hunger")
require(reshape2)
tmp <- melt(dat, id.vars = "x", measure.vars = c("Age", "Revenge", "Homicide", "Hunger"))
require(ggplot2)
ggplot(tmp,aes(x, value)) +
geom_point(aes(colour = factor(variable))) +
xlab("time") +
ylab("units") +
ggtitle("My CSV file") +
labs(colour = "my variables")
![在此处输入图像描述](https://i.stack.imgur.com/jf3z7.png)
以下是您如何将它与 100 多个 CSV 文件一起使用...
files <- (dir("C:/my-csv-files", recursive=TRUE, full.names=TRUE, pattern="\\.(csv|CSV)$"))
listcsvs <- lapply(files, function(i) read.csv(i, stringsAsFactors = FALSE, skip = 19))
names(listcsvs) <- files
require(reshape2)
require(ggplot2)
for (i in 1:length(files)) {
tmp <- melt(dat, id.vars = "x", measure.vars = c("y", "y.1", "y.2", "y.3"))
print( ggplot(tmp,aes(x, value)) +
geom_point(aes(colour = factor(variable))) +
xlab("time") +
ylab("units") +
ggtitle(names(listcsvs[i])) )
)
}