我有一个大致如下结构的数据集:
case Year 2001 2002 2003 2004
1 2003 0 0 0 3
2 2002 0 5 3 2
3 2001 3 3 2 2
我正在尝试对其进行重组,以便每一列代表从“年”变量开始计算的第一年、第二年(等等),即:
case Year yr1 yr2 yr3 yr4
1 2003 0 3 0 0
2 2002 5 3 2 0
3 2001 3 3 2 2
此代码下载数据集并尝试@akrun 建议的解决方案,但失败了。
library("devtools")
df1 <- source_gist("b4c44aa67bfbcd6b72b9")
df1[-(1:2)] <- do.call(rbind,lapply(seq_len(nrow(df1)), function(i) {x <- df1[i, ]; x1 <- unlist(x[-(1:2)]); indx <- which(!is.na(x1))[1]; i <- as.numeric(names(indx))-x[,2]+1; x2 <- x1[!is.na(x1)]; x3 <- rep(NA, length(x1)); x3[i:(i+length(x2)-1)]<- x2; x3}))
这会产生:
Error in i:(i + length(x2) - 1) : NA/NaN argument
In addition: Warning message:
In FUN(1:234[[1L]], ...) : NAs introduced by coercion
如何转换数据,使每一列代表第一年、第二年(等等),从每一行的“年”变量中的值开始计算?
最佳答案
这里有一个可能性:
library(dplyr)
library(reshape2)
df %>%
melt(id.vars = c("case", "Year")) %>%
mutate(variable = as.numeric(as.character(variable)),
yr = variable - Year + 1) %>%
filter(variable >= Year) %>%
dcast(case + Year ~ yr, fill = 0)
# case Year 1 2 3 4
# 1 1 2003 0 3 0 0
# 2 2 2002 5 3 2 0
# 3 3 2001 3 3 2 2
数据:
df <- structure(list(case = 1:3, Year = c(2003L, 2002L, 2001L), `2001` = c(0L,
0L, 3L), `2002` = c(0L, 5L, 3L), `2003` = c(0L, 3L, 2L), `2004` = c(3L,
2L, 2L)), .Names = c("case", "Year", "2001", "2002", "2003",
"2004"), class = "data.frame", row.names = c(NA, -3L))
关于重新排列纵向数据,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/28769805/