传播重复的标识符(使用tidyverse和%>%)

Question

我的数据如下:

我想让它看起来像这样:

我想使用%>% - chaining在tidyverse中执行此操作.

df <- 
structure(list(id = c(2L, 2L, 4L, 5L, 5L, 5L, 5L), start_end = structure(c(2L, 
1L, 2L, 2L, 1L, 2L, 1L), .Label = c("end", "start"), class = "factor"), 
    date = structure(c(6L, 7L, 3L, 8L, 9L, 10L, 11L), .Label = c("1979-01-03", 
    "1979-06-21", "1979-07-18", "1989-09-12", "1991-01-04", "1994-05-01", 
    "1996-11-04", "2005-02-01", "2009-09-17", "2010-10-01", "2012-10-06"
    ), class = "factor")), .Names = c("id", "start_end", "date"
), row.names = c(3L, 4L, 7L, 8L, 9L, 10L, 11L), class = "data.frame")

我尝试过的:

data.table::dcast( df, formula = id ~ start_end, value.var = "date", drop = FALSE )  # does not work because it summarises the data

tidyr::spread( df, start_end, date )  # does not work because of duplicate values


df$id2 <- 1:nrow(df)
tidyr::spread( df, start_end, date ) # does not work because the dataset now has too many rows.

这些问题没有回答我的问题:

使用包含行的重复标识符的扩展 (因为它们汇总)

R:在具有重复项的数据框上传播函数 (因为它们将值粘贴在一起)

用"登录""注销"次数重新整理R中的数据(因为没有特别要求/回答使用tidyverse和链接)

Answer 1

我们可以用tidyverse.在按'start_end','id'分组后,创建一个序列列'ind',然后spread从'long'到'wide'格式

library(dplyr)
library(tidyr)
df %>%
   group_by(start_end, id) %>%
   mutate(ind = row_number()) %>%
   spread(start_end, date) %>% 
   select(start, end)
#     id      start        end
#* <int>     <fctr>     <fctr>
#1     2 1994-05-01 1996-11-04
#2     4 1979-07-18         NA
#3     5 2005-02-01 2009-09-17
#4     5 2010-10-01 2012-10-06