我有一个数据框A，如下所示，其中列Info缺少一些信息，例如Sample2没有其他颜色，白色或黑色：
可复制的示例：
A <- structure(list(Sample = structure(1:7, .Label = c("Sample1",
"Sample2", "Sample3", "Sample4", "Sample5", "Sample6", "Sample7"
), class = "factor"), Description = structure(c(7L, 3L, 4L, 2L,
6L, 1L, 5L), .Label = c("37 years, female, white, alive, 257 days",
"43 years, male, white, stage:iiic, alive, 598 days", "53 years, male, stage:iiib, alive, 792 days",
"68 years, female, white, stage:iiic, dead, 740 days", "69 years, female, black or african american, stage:iia, alive, 627 days",
"74 years, white, stage:i, alive, 1001 days", "82 years, female, white, stage:iiib, alive, 1419 days"
), class = "factor")), class = "data.frame", row.names = c(NA,
-7L))
数据帧A如下所示：
Sample Info
Sample1 82 years, female, white, stage:iiib, alive, 1419 days
Sample2 53 years, male, stage:iiib, alive, 792 days
Sample3 68 years, female, white, stage:iiic, dead, 740 days
Sample4 43 years, male, white, stage:iiic, alive, 598 days
Sample5 74 years, white, stage:i, alive, 1001 days
Sample6 37 years, female, white, alive, 257 days
Sample7 69 years, female, black, stage:iia, alive, 627 days
要将Info列分成多个列，我使用了如下的separate函数
library(dplyr)
library(tidyr)
A2 <- separate(A, 'Info', paste("Info", 1:6, sep="_"), sep=",", extra="drop")
但是新列看起来像下面这样不均匀：
Sample Info_1 Info_2 Info_3 Info_4 Info_5 Info_6
Sample1 82 years female white stage:iiib alive 1419 days
Sample2 53 years male stage:iiib alive 792 days NA
Sample3 68 years female white stage:iiic dead 740 days
Sample4 43 years male white stage:iiic alive 598 days
Sample5 74 years white stage:i alive 1001 days NA
Sample6 37 years female white alive 257 days NA
Sample7 69 years female black stage:iia alive 627 days
我希望output如下所示，其中缺少的信息需要为空白或NA，最后一列仅显示其中没有任何单词days的数字：
Sample Info_1 Info_2 Info_3 Info_4 Info_5 Info_6
Sample1 82 years female white stage:iiib alive 1419
Sample2 53 years male stage:iiib alive 792
Sample3 68 years female white stage:iiic dead 740
Sample4 43 years male white stage:iiic alive 598
Sample5 74 years white stage:i alive 1001
Sample6 37 years female white alive 257
Sample7 69 years female black stage:iia alive 627
感谢您的帮助。谢谢
答案 0 :(得分：3)
使用结尾处“注释”中可重复显示的数据，我们可以将read.pattern与指示的模式pat一起使用，然后删除垃圾列（其他所有列）。如果您不要求列名与问题中的名称完全相同，则可以省略标记为##的行。
library(gsubfn)
pat <-
"((\\d+ years), )?((female|male), )?((white|black), )?((stage:\\S+), )?((alive|dead), )?((\\d+) days)?"
r <- read.pattern(text = as.character(DF$Info), pattern = pat, as.is = TRUE)
DF2 <- cbind(Sample = DF$Sample, r[c(FALSE, TRUE)], stringsAsFactors = FALSE)
nc <- ncol(DF2) ##
names(DF2)[-1] <- paste0("Info_", 1:(nc-1)) ##
DF2
给予：
Sample Info_1 Info_2 Info_3 Info_4 Info_5 Info_6
1 Sample1 82 years female white stage:iiib alive 1419
2 Sample2 53 years male stage:iiib alive 792
3 Sample3 68 years female white stage:iiic dead 740
4 Sample4 43 years male white stage:iiic alive 598
5 Sample5 74 years white stage:i alive 1001
6 Sample6 37 years female white alive 257
7 Sample7 69 years female black stage:iia alive 627
可重复形式的输入DF如下。
Lines <- "
Sample;Info
Sample1;82 years, female, white, stage:iiib, alive, 1419 days
Sample2;53 years, male, stage:iiib, alive, 792 days
Sample3;68 years, female, white, stage:iiic, dead, 740 days
Sample4;43 years, male, white, stage:iiic, alive, 598 days
Sample5;74 years, white, stage:i, alive, 1001 days
Sample6;37 years, female, white, alive, 257 days
Sample7;69 years, female, black, stage:iia, alive, 627 days"
DF <- read.table(text = Lines, header = TRUE, sep = ";", as.is = TRUE, strip.white = TRUE)
答案 1 :(得分：2)
这是一个主意。我相信有更好的方法，但这是一个开始。
我们可以使用int *中的printf("%d",*b);
来拆分从完整记录开始的列。关键是设置可识别且有意义的列名。之后，我们用*b删除行，并将其从原始数据框中删除。然后我们假设某些列丢失了，可以再次执行int。最终，我们可以满足所有缺失的条件并适当地将它们分开。最后一步是合并所有子集数据帧。
如果缺少许多不同的列组件，则此方法可能太麻烦了。但是，如果您确定可能会丢失什么。我们可以设计一个函数并将所有这些步骤包装在函数中。
extract数据
tidyr