r - 在 R 中处理具有相同 Id(键)列值的多行

Question

我正在处理人口普查数据。数据集的样子是:

Household-Id    Member-Type    Education    Birth
1               Father         12           1955
1               Mother         16           1963
1               Child          16           1986
1               Child          12           1995
2               Father         12           1950
2               Mother         9            1955
2               Child          18           1982
2               Child          14           1985
2               Child          16           1975
3               Father         16           1962
3               Mother         14           1965
3               Child          16           1990

我希望它看起来像:

Household-Id    Member-Type    Education    Birth    Mother-Education    Birth-Order 
1               Father         12           1955     
1               Mother         16           1963
1               Child          16           1986     16                  1
1               Child          12           1995     16                  2
2               Father         12           1950
2               Mother         9            1955
2               Child          18           1982     9                   1
2               Child          14           1985     9                   2
2               Child          16           1975     9                   3
3               Father         16           1962
3               Mother         14           1965
3               Child          16           1990     14                  1

据我所知，R 不像 Java 或 C 语言那样支持循环操作，而且我真的不知道如何做到这一点!

Answer 1

您从哪里听说 R 不支持循环？确实如此——这种特殊情况听起来最适合 data.table(内部使用循环)

install.packages("data.table")
library(data.table)
dat = as.data.table(YourDataFrame)

dat[Member.Type == "Child", Birth_Order:=rank(Birth) ,by=Household.Id]
dat[, MotherEducation := Education[Member.Type=="Mother"] , by=Household.Id]
dat[Member.Type != "Child", MotherEducation := NA]
dat
#   Household.Id Member.Type Education Birth MotherEducation Birth_Order
#  1:            1      Father        12  1955              NA          NA
#  2:            1      Mother        16  1963              NA          NA
#  3:            1       Child        16  1986              16           1
#  4:            1       Child        12  1995              16           2
#  5:            2      Father        12  1950              NA          NA
#  6:            2      Mother         9  1955              NA          NA
#  7:            2       Child        18  1982               9           2
#  8:            2       Child        14  1985               9           3
#  9:            2       Child        16  1975               9           1
# 10:            3      Father        16  1962              NA          NA
# 11:            3      Mother        14  1965              NA          NA
# 12:            3       Child        16  1990              14           1