R - 将一列数据帧拆分为多列

时间:2022-10-16 22:54:23

I have a dataframe that is a column with all the state abbreviations:

我有一个数据框,它是一个包含所有州缩写的列:

Name
AK
AL
AR
AZ
CO
CT
DC
FL

I want to take this column and split it into multiple columns such that no column has more than 5 cells.

我想取这个列并将其拆分成多列,这样任何列都不会超过5个单元格。

Name1    Name2
AK       CT
AL       DC
AR       FL
AZ
CO

I can create the code for what I want to do, but there has to be a better way:

我可以为我想要做的事创建代码,但必须有更好的方法:

states <- as.data.frame(state.abb)

new.table <- as.data.frame(states[1:5,])

i <- 6
k <- 2

repeat{
  new.table[,k] <- as.data.frame(states[(i):(i+4),])
  i <- i + 5
  k <- k + 1
  if(i>nrow(states)){
    break
  }
}

2 个解决方案

#1


5  

If NA is okay to use for the blank values, then we can do the following. Assuming your data is named df, we can first create a vector of values to be used for splitting the data.

如果NA可以用于空白值,那么我们可以执行以下操作。假设您的数据名为df,我们可以先创建一个值向量来分割数据。

(x <- rep(1:ceiling(nrow(df) / 5), each = 5, length.out = nrow(df)))
# [1] 1 1 1 1 1 2 2 2

Now we can split the data, loop the resulting list to make each element length 5, and coerce to data frame. Column names are created on-the-fly here. It may be more efficient to create them afterward.

现在我们可以分割数据,循环结果列表以使每个元素长度为5,并强制转换为数据帧。列名在此处即时创建。之后创建它们可能更有效。

as.data.frame(lapply(split(df$Name, paste0(names(df), x)), "length<-", 5))
#   Name1 Name2
# 1    AK    CT
# 2    AL    DC
# 3    AR    FL
# 4    AZ  <NA>
# 5    CO  <NA>

#2


7  

Similar to @RichScriven's concept, but using a matrix to deal with the reshaping:

与@ RichScriven的概念类似,但使用矩阵来处理重塑:

columniser <- function(x, n) {
  m <- matrix(NA, nrow=n, ncol=ceiling(length(x)/n) )
  m[1:length(x)] <- x
  as.data.frame(m)
}

columniser(states$state.abb, 5)
#  V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
#1 AL CO HI KS MA MT NM OK SD  VA
#2 AK CT ID KY MI NE NY OR TN  WA
#3 AZ DE IL LA MN NV NC PA TX  WV
#4 AR FL IN ME MS NH ND RI UT  WI
#5 CA GA IA MD MO NJ OH SC VT  WY

columniser(1:12, 5)
#  V1 V2 V3
#1  1  6 11
#2  2  7 12
#3  3  8 NA
#4  4  9 NA
#5  5 10 NA

#1


5  

If NA is okay to use for the blank values, then we can do the following. Assuming your data is named df, we can first create a vector of values to be used for splitting the data.

如果NA可以用于空白值,那么我们可以执行以下操作。假设您的数据名为df,我们可以先创建一个值向量来分割数据。

(x <- rep(1:ceiling(nrow(df) / 5), each = 5, length.out = nrow(df)))
# [1] 1 1 1 1 1 2 2 2

Now we can split the data, loop the resulting list to make each element length 5, and coerce to data frame. Column names are created on-the-fly here. It may be more efficient to create them afterward.

现在我们可以分割数据,循环结果列表以使每个元素长度为5,并强制转换为数据帧。列名在此处即时创建。之后创建它们可能更有效。

as.data.frame(lapply(split(df$Name, paste0(names(df), x)), "length<-", 5))
#   Name1 Name2
# 1    AK    CT
# 2    AL    DC
# 3    AR    FL
# 4    AZ  <NA>
# 5    CO  <NA>

#2


7  

Similar to @RichScriven's concept, but using a matrix to deal with the reshaping:

与@ RichScriven的概念类似,但使用矩阵来处理重塑:

columniser <- function(x, n) {
  m <- matrix(NA, nrow=n, ncol=ceiling(length(x)/n) )
  m[1:length(x)] <- x
  as.data.frame(m)
}

columniser(states$state.abb, 5)
#  V1 V2 V3 V4 V5 V6 V7 V8 V9 V10
#1 AL CO HI KS MA MT NM OK SD  VA
#2 AK CT ID KY MI NE NY OR TN  WA
#3 AZ DE IL LA MN NV NC PA TX  WV
#4 AR FL IN ME MS NH ND RI UT  WI
#5 CA GA IA MD MO NJ OH SC VT  WY

columniser(1:12, 5)
#  V1 V2 V3
#1  1  6 11
#2  2  7 12
#3  3  8 NA
#4  4  9 NA
#5  5 10 NA