作為R語(yǔ)言新手，在使用R語(yǔ)言的過(guò)程中遇到了很多的問(wèn)題露氮。本文總結(jié)了幾個(gè)常見(jiàn)問(wèn)題的解決方法，希望對(duì)需要的人能有所幫助近哟。

R語(yǔ)言幾個(gè)解決方法總結(jié)

初學(xué)R語(yǔ)言會(huì)遇到很多問(wèn)題盐股，都是細(xì)細(xì)碎碎的小點(diǎn)钱豁，但是最困難的是，以前也沒(méi)有系統(tǒng)的學(xué)過(guò)Matlab疯汁，對(duì)于類似語(yǔ)言的使用尤其是在一些思想上一時(shí)半會(huì)轉(zhuǎn)變不過(guò)來(lái)牲尺。只好邊學(xué)邊用先積累了，這里把遇到的一些問(wèn)題總結(jié)一下記錄下來(lái)幌蚊。每個(gè)問(wèn)題都是獨(dú)立的谤碳，彼此之間沒(méi)有什么聯(lián)系。

sprintf調(diào)用C函數(shù)sprintf溢豆，可以用來(lái)格式化字符串

> sprintf("%04d", 1)
[1] "0001"
> sprintf("%04d", 104)
[1] "0104"
> sprintf("%010d", 104)
[1] "0000000104"

安裝data.table

data.table是個(gè)好用的包蜒简，安裝方法可以參考這里：https://class.coursera.org/getdata-008/forum/thread?thread_id=58

Here is how I installed the data.table package:

Used my browser to download data.table_1.9.4.zip from page http://cran.r-project.org/web/packages/data.table/index.html

Put the downloaded file in my R working directory.

> install.packages("data.table_1.9.4.zip", repos=NULL)
> install.packages("plyr")
> install.packages("Rcpp")
> install.packages("rshape2")
> install.packages("chron")

Once done with that, I could do:
> library(data.table)
and everything else worked.

order的用法

對(duì)一個(gè)vector或者data.frame排序可以使用order函數(shù)，關(guān)于order和rank函數(shù)的使用和結(jié)果解釋需要注意：

You can use the order() function directly without resorting to add-on tools -- see this simpler answer which uses a trick right from the top of the example(order) code:
R> dd[with(dd, order(-z, b)), ]
    b x y z
4 Low C 9 22 Med D 3 11  Hi A 8 13  Hi A 9 1
Edit some 2+ years later: It was just asked how to do this by column index. The answer is to simply pass the desired sorting column(s) to the order() function:
R> dd[ order(-dd[,4], dd[,1]), ]
    b x y z
4 Low C 9 22 Med D 3 11  Hi A 8 13  Hi A 9 1
R> 
rather than using the name of the column (and with() for easier/more direct access).

關(guān)于order函數(shù)結(jié)果的解釋：

The definition of order is that a[order(a)] is in increasing order. This works with your example, where the correct order is the fourth, second, first, then third element.
You may have been looking for rank, which returns the rank of the elements
R> a <- c(4.1, 3.2, 6.1, 3.1)
R> order(a)
[1] 4 2 1 3
R> rank(a)
[1] 3 2 4 1
so rank tells you what order the numbers are in, order tells you how to get them in ascending order.
plot(a, rank(a)/length(a)) will give a graph of the CDF. To see why order is useful, though, try plot(a, rank(a)/length(a),type="S") which gives a mess, because the data are not in increasing order
If you did
oo<-order(a)
plot(a[oo],rank(a[oo])/length(a),type="S")
or simply
oo<-order(a)
plot(a[oo],(1:length(a))/length(a)),type="S")
you get a line graph of the CDF.

判斷vector中是否有某一個(gè)元素

v <- c('a','b','c','e')
'b' %in% v
## returns TRUE

match('b',v)
## returns the first location of 'b', in this case: 2

> x <- sample(1:10)
> x
 [1]  4  5  9  3  8  1  6 10  7  2
> match(c(4,8),x)
 [1] 1 5
match only returns the first encounter of a match, as you requested.
For multiple matching, %in% is the way to go :
> x <- sample(1:4,10,replace=T)
> x
 [1] 3 4 3 3 2 3 1 1 2 2
> which(x %in% c(2,4))[1]  2  5  9 10

關(guān)于給vector中添加元素

Here are several ways to do it. All of them are discouraged. Appending to an object in a for loop causes the entire object to be copied on every iteration, which causes a lot of people to say "R is slow", or "R loops should be avoided".

# one way
for (i in 1:length(values))
  vector[i] <- values[i]

# another way
for (i in 1:length(values))
  vector <- c(vector, values[i])

# yet another way?!?
for (v in values)
  vector <- c(vector, v)
# ... more ways

help("append") would have answered your question and saved the time it took you to write this question (but would have caused you to develop bad habits). ;-)

Note that vector <- c() isn't an empty vector; it's NULL. If you want an empty character vector, use vector <- character().

Also note, as BrodieG pointed out in the comments: if you absolutely must use a for loop, then at least pre-allocate the entire vector before the loop. This will be much faster than appending for larger vectors.

set.seed(21)
values <- sample(letters, 1e4, TRUE)
vector <- character(0)# slow
system.time( for (i in 1:length(values)) vector[i] <- values[i] )
#  user  system elapsed
#  0.340  0.000  0.343
vector <- character(length(values))# fast(er)
system.time( for (i in 1:length(values)) vector[i] <- values[i] )
#  user  system elapsed 
#  0.024  0.000  0.023

要注意的是漩仙，這里有性能方面的問(wèn)題臭蚁。

刪除data.frame中的一列

> head(data)
   chr       genome region
1 chr1 hg19_refGene    CDS
2 chr1 hg19_refGene   exon
3 chr1 hg19_refGene    CDS
4 chr1 hg19_refGene   exon
5 chr1 hg19_refGene    CDS
6 chr1 hg19_refGene   exon



You can set it to NULL.
> Data$genome <- NULL
> head(Data)
   chr region
1 chr1    CDS
2 chr1   exon
3 chr1    CDS
4 chr1   exon
5 chr1    CDS
6 chr1   exon

As pointed out in the comments, here are some other possibilities:
Data[2] <- NULL    # Wojciech Sobala
Data[[2]] <- NULL  # same as above
Data <- Data[,-2]  # Ian Fellows
Data <- Data[-2]   # same as above

You can remove multiple columns via:    
Data[1:2] <- list(NULL)  # Marek
Data[1:2] <- NULL        # does not work!

Be careful with matrix-subsetting though, as you can end up with a vector:    
Data <- Data[,-(2:3)]             # vector
Data <- Data[,-(2:3),drop=FALSE]  # still a data.frame

從字符串中去除括號(hào)

string <- "log(M)"
gsub("log", "", string) # Works just fine
gsub("log(", "", string) #breaks
# Error in gsub("log(", "", test) : 
#   invalid regular expression 'log(', reason 'Missing ')''

Escape the parenthesis with a double-backslash:
要用雙斜線來(lái)轉(zhuǎn)義括號(hào)
gsub("log\\(", "", string)