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我有一个关于职位晋升的数据集。对于每个人，我都有关于他们何时被公司聘用、晋升和离开公司的确切数据。我也有几个特点。我正在使用 r。

SubjectID Entry     Stage1    Stage2    Stage3    Stage4   Exit     Race  Edu
   1      1/12/1990 1/12/1990 1/12/1990  4/3/1994          5/5/1994 B     M
   2      1/17/1991 1/17/1991 3/3/1991   3/18/1992 1/1/1993         W     C 
   3      1/24/1991 1/24/1991 5/6/1994                              B     M

我想将这些数据转换成一个长的纵向数据集，其中每个日期报告个人所处的阶段，同时还报告时间不变的特征。我的结束日期是 1995 年 1 月 1 日，之后没有观察到。我已经查看了 reshape 包，但它没有我需要的东西。

我的数据：

结构（列表（ï..Name = 结构（c（2L，1L，4L，3L），.Label = c（“Ademulegun，Sauel Adesujo”，“Bassey，惠灵顿 Umo”，“Imo，UO”，“Lawan， Umar"), class = "factor"), Mons = c(0L, 0L, 0L, 0L), Sandhurst = c(0L, 0L, 1L, 0L), Entry = structure(c(2L, 3L, 1L, 4L) ), .Label = c("2/6/1953", "4/30/1949", "6/11/1949", "6/4/1955"), class = "factor"), Second.Lieutenant =结构（c（2L，3L，1L，4L），.Label = c（“2/6/1953”，“4/30/1949”，“6/11/1949”，“6/4/1955” ), class = "factor"), Lieutenant = structure(c(2L, 1L, 4L, 3L), .Label = c("12/20/1949", "4/30/1949", "5/3/ 1958", "8/1/1955"), class = "factor"),船长=结构（c（2L，3L，1L，4L），.Label = c（“”，“2/7/1951”，“3/5/1952”，“5/3/1958”），类= "因子"), 主要 = 结构 (c(4L, 3L, 1L, 2L), .Label = c("", "1/15/1963", "12/27/1958", "6/21/1957 " ), class = "factor"), Lieutenant.Colonel = structure(c(4L, 3L, 1L, 2L), .Label = c("", "1/15/1963", "10/3/1962" , "8/30/1962"), class = "factor"), 上校 = structure(c(3L, 2L, 1L, 1L), .Label = c("", "10/3/1962", "2 /26/1966"), class = "factor"), Brigadier.General = structure(c(3L, 2L, 1L, 1L), .Label = c("", "10/3/1962", "2/ 26/1966"), 类 = "因素"),出发=结构（c（2L，1L，3L，4L），.Label = c（“1/15/1966”，“11/1/1966”，“5/8/1956”，“7/6/1967 "), class = "factor"), 种族 = structure(c(1L, 4L, 3L, 2L), .Label = c("Efik", "Igbo", "Kanuri", "Yoruba"), class = "因子")), 类 = "data.frame", row.names = c(NA, -4L))

我正在寻找这样的东西：

Name  Date       Mons Sandhurst Ethnicity Rank
Bassey 4/30/1949  0     0       Efik      Lieutenant
Bassey 5/1/1949   0     0       Efik      Lieutenant
....
Bassey 2/7/1951   0     0       Efik      Captain
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1 回答 1

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data.table 解决方案

library(data.table)

样本数据

df <- structure(list(Name = structure(c(2L, 1L, 4L, 3L), .Label = c("Ademulegun, Sauel Adesujo", "Bassey, Wellington Umo", "Imo, U. O.", "Lawan, Umar"), class = "factor"), Mons = c(0L, 0L, 0L, 0L), Sandhurst = c(0L, 0L, 1L, 0L), Entry = structure(c(2L, 3L, 1L, 4L), .Label = c("2/6/1953", "4/30/1949", "6/11/1949", "6/4/1955"), class = "factor"), Second.Lieutenant = structure(c(2L, 3L, 1L, 4L), .Label = c("2/6/1953", "4/30/1949", "6/11/1949", "6/4/1955"), class = "factor"), Lieutenant = structure(c(2L, 1L, 4L, 3L), .Label = c("12/20/1949", "4/30/1949", "5/3/1958", "8/1/1955"), class = "factor"), Captain = structure(c(2L, 3L, 1L, 4L), .Label = c("", "2/7/1951", "3/5/1952", "5/3/1958"), class = "factor"), Major = structure(c(4L, 3L, 1L, 2L), .Label = c("", "1/15/1963", "12/27/1958", "6/21/1957" ), class = "factor"), Lieutenant.Colonel = structure(c(4L, 3L, 1L, 2L), .Label = c("", "1/15/1963", "10/3/1962", "8/30/1962" ), class = "factor"), Colonel = structure(c(3L, 2L, 1L, 1L ), .Label = c("", "10/3/1962", "2/26/1966"), class = "factor"), Brigadier.General = structure(c(3L, 2L, 1L, 1L), .Label = c("", "10/3/1962", "2/26/1966"), class = "factor"), Depature = structure(c(2L, 1L, 3L, 4L), .Label = c("1/15/1966", "11/1/1966", "5/8/1956", "7/6/1967"), class = "factor"), ethnicity = structure(c(1L, 4L, 3L, 2L), .Label = c("Efik", "Igbo", "Kanuri", "Yoruba" ), class = "factor")), class = "data.frame", row.names = c(NA, -4L))

使用 data.tables 快速重塑melt

library( data.table )

data.table::melt( data = setDT( df ),
                  id.vars = c("Name", "Mons", "Sandhurst", "ethnicity" ),
                  value.name = "Date",
                  variable.name = "Rank",
                  na.rm = TRUE )

结果

#                         Name Mons Sandhurst ethnicity               Rank       Date
# 1:    Bassey, Wellington Umo    0         0      Efik              Entry  4/30/1949
# 2: Ademulegun, Sauel Adesujo    0         0    Yoruba              Entry  6/11/1949
# 3:               Lawan, Umar    0         1    Kanuri              Entry   2/6/1953
# 4:                Imo, U. O.    0         0      Igbo              Entry   6/4/1955
# 5:    Bassey, Wellington Umo    0         0      Efik  Second.Lieutenant  4/30/1949
# 6: Ademulegun, Sauel Adesujo    0         0    Yoruba  Second.Lieutenant  6/11/1949
# 7:               Lawan, Umar    0         1    Kanuri  Second.Lieutenant   2/6/1953
# 8:                Imo, U. O.    0         0      Igbo  Second.Lieutenant   6/4/1955
# 9:    Bassey, Wellington Umo    0         0      Efik         Lieutenant  4/30/1949

根据需要重新排序...

注意： 如果您希望“空”日期在熔融数据中消失，请确保将 puntNA放在源数据中的空日期中。na.rm = TRUE在熔融功能中，然后将其删除。

于 2018-10-05T06:57:44.830 回答