我有一个大致这样的数据集:
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,以使每一列都代表从“年”变量开始计算的第一年,第二年(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使用@akrun建议的解决方案,但失败。
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}))
这将产生:
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,以使每一列都代表从每一年“ Year”变量中的值开始计算的第一年,第二年(等等)?
最佳答案
这将创建您要查找的操作。
library("devtools")
df1 <- source_gist("b4c44aa67bfbcd6b72b9")
temp <- df1[[1]]
library(dplyr); library(tidyr); library(stringi)
temp <- temp %>%
gather(new.Years, X, -Year) %>% # convert rows to one column
mutate(Year.temp=paste0(rownames(temp), "-", Year)) %>% # concatenate the Year with row number to make them unique
mutate(new.Years = as.numeric(gsub("X", "", new.Years)), diff = new.Years-Year+1) %>% # calculate the difference to get the yr0 yr1 and so on
mutate(diff=paste0("yr", stri_sub(paste0("0", (ifelse(diff>0, diff, 0))), -2, -1))) %>% # convert the differences in Yr01 ...
select(-new.Years) %>% filter(diff != "yr00") %>% # drop new.Years column
spread(diff, X) %>% # convert column to rows
select(-Year.temp) # Drop Year.temp column
temp[is.na(temp)] <- 0 # replace NA with 0
temp %>% View
请注意,这可以使用长达99年。
关于r - 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/