将多个 csv 文件（类似列）与 r 中的选择性行和列合并为一个

Question

I have around 300-500 CSV files with some character information at the beginning and two-column as numeric data. I want to make one data.frame with all the numeric values in Such a way that I have column X once with multiple Y without the character rows.

**File1** has two-column and more than a thousand rows: an example looks like 

info   info
info   info
info   info
X      Y
1      50.3
2      56.2
3      96.5
4      56.4
5      65.2
info   0

**File2**
info   info
info   info
info   info
X      Y
1      46.3
2      65.2
3      21.6
4      98.2
5      25.3
info   0

Only Y values are changing from file to file, I want to add all the files in one file with selective rows and make a data frame. Such as I want as a data frame.

X      Y1      Y2
1      46.3   50.3
2      65.2   56.2
3      21.6   96.5
4      98.2   56.4
5      25.3   65.2

I tried
files <- list.files(pattern="*.csv")
l <- list()
for (i in 1:length(files)){
 l[[i]] <- read.csv(files[i], skip = 3)
 }
data.frame(l)


This gives me

X1      Y1   X2    Y2
1      46.3  1    50.3
2      65.2  2    56.2
3      21.6  3    96.5
4      98.2  4    56.4
5      25.3  5    65.2
info   0     info 0

How can I skip the last row and column X as the first column only (since X values do not change)

Answer 1

Define a function Read that reads one file removing all lines that do not start with a digit. We use sep="," to specify that the fields in each file are comma separated. Then use Read with read.zoo to read and merge the files giving zoo object z . Finally either use it as a zoo object or convert it to a data frame as shown.

library(zoo)

Read <- function(f) {
  read.table(text = grep("^\\d", readLines(f), value = TRUE), sep = ".")
}
z <- read.zoo(Sys.glob("*.csv"), read = Read)
DF <- fortify.zoo(z)