R 返回因子变量第一次和最后一次出现的日期

问题

我有一个数据框架，其中每一行都标记着公司之间的交换，公司在给定的日期给予和接受某些东西（他们可以给予不同的公司或自己）。由此，我想创建一个新的数据框，其中的列指示公司何时开始提供、何时停止提供、何时开始接收以及何时停止接收。下面是我开始介绍的示例数据框：

样本起始数据

samp <- structure(list(giver = structure(c(1L, 2L, 6L, 3L, 1L, 3L, 4L, 1L, 6L, 1L, 5L), .Label = c("A", "B", "C", "X", "Y", "Z"), class = "factor"), receiver = structure(c(1L, 2L, 2L, 3L, 1L, 3L, 3L, 1L, 2L, 1L, 2L), .Label = c("A", "B", "C"), class = "factor"), date = structure(c(1L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 9L), .Label = c("2000-01-01", "2000-01-02", "2000-01-03", "2000-01-04", "2000-01-05", "2000-01-06", "2000-01-07", "2000-01-08", "2000-01-09"), class = "factor")), .Names = c("giver", "receiver", "date"), class = "data.frame", row.names = c(NA, -11L))
samp$date <- as.Date(samp$date, "%Y-%m-%d") # Format date variable

samp 
giver receiver   date
A        A     2000-01-01
B        B     2000-01-01
Z        B     2000-01-02
C        C     2000-01-03
A        A     2000-01-04
C        C     2000-01-05
X        C     2000-01-06
A        A     2000-01-07
Z        B     2000-01-08
A        A     2000-01-09
Y        B     2000-01-09

desire <- structure(list(company = structure(1:6, .Label = c("A", "B", "C", "X", "Y", "Z"), class = "factor"), start.giving = structure(c(1L, 1L, 3L, 4L, 5L, 2L), .Label = c("2000-01-01", "2000-01-02", "2000-01-03", "2000-01-05", "2000-01-09"), class = "factor"), stop.giving = structure(c(5L, 1L, 2L, 3L, 5L, 4L), .Label = c("2000-01-01", "2000-01-05", "2000-01-06", "2000-01-08", "2000-01-09"), class = "factor"), start.receiving = structure(c(1L, 1L, 2L, NA, NA, NA), .Label = c("2000-01-01", "2000-01-03"), class = "factor"), stop.receiving = structure(c(2L, 2L, 1L, NA, NA, NA), .Label = c("2000-01-06", "2000-01-09"), class = "factor")), .Names = c("company", "start.giving", "stop.giving", "start.receiving", "stop.receiving"), class = "data.frame", row.names = c(NA, -6L))

desire 
company start.giving stop.giving start.receiving stop.receiving
A       2000-01-01   2000-01-09      2000-01-01     2000-01-09
B       2000-01-01   2000-01-01      2000-01-01     2000-01-09
C       2000-01-03   2000-01-05      2000-01-03     2000-01-06
X       2000-01-05   2000-01-06            <NA>           <NA>
Y       2000-01-09   2000-01-09            <NA>           <NA>
Z       2000-01-02   2000-01-08            <NA>           <NA>

---

这可以通过

聚合

和

合并

命令在基本R中完成：

# Import starting sample data
samp <- structure(list(giver = structure(c(1L, 2L, 6L, 3L, 1L, 3L, 4L, 1L, 6L, 1L, 5L), .Label = c("A", "B", "C", "X", "Y", "Z"), class = "factor"), receiver = structure(c(1L, 2L, 2L, 3L, 1L, 3L, 3L, 1L, 2L, 1L, 2L), .Label = c("A", "B", "C"), class = "factor"), date = structure(c(1L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 9L), .Label = c("2000-01-01", "2000-01-02", "2000-01-03", "2000-01-04", "2000-01-05", "2000-01-06", "2000-01-07", "2000-01-08", "2000-01-09"), class = "factor")), .Names = c("giver", "receiver", "date"), class = "data.frame", row.names = c(NA, -11L))
samp$date <- as.Date(samp$date, "%Y-%m-%d") # Format date variable

# Find first and last occurrence by date
g1 <- aggregate(samp$date, list(samp$giver), min)
colnames(g1)[1] = "company"
colnames(g1)[2] = "start.giving"

g2 <- aggregate(samp$date, list(samp$giver), max)
colnames(g2)[1] = "company"
colnames(g2)[2] = "stop.giving"

s1 <- aggregate(samp$date, list(samp$receiver), min)
colnames(s1)[1] = "company"
colnames(s1)[2] = "start.receiving"

s2 <- aggregate(samp$date, list(samp$receiver), max)
colnames(s2)[1] = "company"
colnames(s2)[2] = "stop.receiving"

# Merge data frames by company name
a1 <- merge(g1, g2, by=c("company"))
b1 <- merge(s1, s2, by=c("company"))
c1 <- merge(a1, b1, by=c("company"), all.x = TRUE)

c1 # Display desired data frame
company start.giving stop.giving start.receiving stop.receiving
 A       2000-01-01  2000-01-09     2000-01-01     2000-01-09
 B       2000-01-01  2000-01-01     2000-01-01     2000-01-09
 C       2000-01-03  2000-01-05     2000-01-03     2000-01-06
 X       2000-01-06  2000-01-06         <NA>           <NA>
 Y       2000-01-09  2000-01-09         <NA>           <NA>
 Z       2000-01-02  2000-01-08         <NA>           <NA>

#导入起始样本数据
samp这里有一个使用
data.table
包的简化版本

library(data.table)
setDT(samp)
Res1 <- samp[, .(start = min(date), stop = max(date)), by = .(company = giver)]
Res2 <- samp[, .(start = min(date), stop = max(date)), by = .(company = receiver)]
merge(Res1, Res2, by = "company", all = TRUE, suffixes = c(".giving", ".receiving"))
#    company start.giving stop.giving start.receiving stop.receiving
# 1:       A   2000-01-01  2000-01-09      2000-01-01     2000-01-09
# 2:       B   2000-01-01  2000-01-01      2000-01-01     2000-01-09
# 3:       C   2000-01-03  2000-01-05      2000-01-03     2000-01-06
# 4:       X   2000-01-06  2000-01-06            <NA>           <NA>
# 5:       Y   2000-01-09  2000-01-09            <NA>           <NA>
# 6:       Z   2000-01-02  2000-01-08            <NA>           <NA>

库（data.table）
setDT（samp）
Res1，下面是另一个使用dcast新功能的版本：

require(data.table) ## v1.9.5+
foo <- function(x, col) {
    ans <- dcast(x, paste(col, "~ ."), value.var="date", fun=list(min, max))
    setnames(ans, c("company", "start", "stop"))
}
setDT(samp)
merge(foo(samp, "giver"), foo(samp, "receiver"), by = "company", 
        all=TRUE, suffixes=c(".giving", ".receiving"))
#    company start.giving stop.giving start.receiving stop.receiving
# 1:       A   2000-01-01  2000-01-09      2000-01-01     2000-01-09
# 2:       B   2000-01-01  2000-01-01      2000-01-01     2000-01-09
# 3:       C   2000-01-03  2000-01-05      2000-01-03     2000-01-06
# 4:       X   2000-01-06  2000-01-06            <NA>           <NA>
# 5:       Y   2000-01-09  2000-01-09            <NA>           <NA>
# 6:       Z   2000-01-02  2000-01-08            <NA>           <NA>

require（data.table）#v1.9.5+
foo该
dplyr
版本：

library("dplyr")
giving <- samp %>% group_by(giver) %>%
    summarise(start.giving=min(date),
              stop.giving=max(date)) %>%
       rename(company=giver)
receiving <- samp %>% group_by(receiver) %>%
    summarise(start.receiving=min(date),
              stop.receiving=max(date)) %>%
       rename(company=receiver)
full_join(giving,receiving)

。。。虽然代码现在不那么透明，实际上也不更短。。。如果你打算经常做这类事情，那是值得的。
在创建
接收
对象时，我认为在
（start.receiving=min（date）），
之后有一个额外的括号。它应该是
（start.receiving=min（date），
，对吗？另外，由于某种原因，我在
full\u join（）
命令中遇到一个错误：“错误：找不到函数'full\u join'”尽管显然已加载了
dplyr
。Thx以进行更正。在最新版本的
dplyr
中，联接/合并函数的名称相当流畅。您可以尝试使用
outer_join（）
。
foo <- function(x,f) {
    ss <- c("start","stop")
    group_by_(x,.dots=f) %>%
       summarise(start=min(date),
                 stop=max(date)) %>%
       rename_(.dots=c(company=f,
                       setNames(ss,paste(ss,f,sep="."))))
 }
 full_join(foo(samp,"giver"),foo(samp,"receiver"))