How to import last 100 rows using read.csv() in R

Question

Hi I've a huge file and i want to import only the last 100 rows from that file. How can we do that using read.csv() or any alternative?

Answer 1

The package R.utils has a function called countLines(). You could do:

l2keep <- 10
nL <- countLines("your.csv")
df <- read.csv("your.csv", header=FALSE, skip=nL-l2keep)

Answer 2

If you are on a *nix system, you are better off using the tail -n 100 command to take the last 100 rows. Anything implemented in R would be slower and potentially much slower is your file is truly huge.

If you are using Windows, you may want to take a look at this SO question .

Answer 3

You could use the nrows and skip arguments in read.csv . Eg if you have a file with 10000 rows and you would only like to import the last 100 rows you could try this:

read.csv("yourfile.csv",nrows=100,skip=9900)

But if it is speed you want, you're probably better off with the solutions given by @Ananda Mahto and @ktdrv

Answer 4

Improvement on @lauratboyer's answer if you want to include headers too:

# read headers only
column_names <- as.vector(t(read.csv("your.csv", header=FALSE, colClasses='character', nrows=1)))

# then last n lines
l2keep <- 10
nL <- R.utils::countLines("your.csv")
df <- read.csv("your.csv", header=FALSE, col.names=column_names, skip=nL-l2keep)

Answer 5

The quick and dirty way that works for me - use fread to read large files while setting select = 1 so that only the first column is read. Then use fread again to read data from the desired rows. Fread is much faster than read.csv or other similar variants. More on fread vs read.csv here: Reason behind speed of fread in data.table package in R

Answer 6

读取文件，使用尾部函数 a <-read.csv（'c：/ ..'）尾部（a，100L）

Answer 7

在read.csv（）中给出适当的跳过参数