R-ddply：汇总时将日期转换为数字

我有一个不同日期的id_客户表。我需要创建一个表，其中包含每个客户端的最大日期和最小日期之间的所有日期。例如，我的表格是：

tbl<-data.frame(id_cliente=c(1,1,1,1,2,3,3,3), 
                fecha=c('2013-01-01', '2013-06-01','2013-05-01', '2013-04-01', 
                        '2013-01-01', '2013-01-01','2013-05-01','2013-04-01'))

tbl$fecha<-as.Date(as.character(tbl$fecha))

我想我可以使用ddply（plyr软件包），所以我创建了一个函数，可以获得月的序列：

meses<-function(xMin, xMax){ 
  seq(from=as.Date(xMin, , '%Y-%m-%d'), to=as.Date(xMax, '%Y-%m-%d'), by='month')}

存储在列表中的日期将转换为数字

我知道我可以把数字转换成日期。因此：

convFecha<-function(x){as.Date(x, origin='1970-01-01')}

我得到了想要的结果：

[[1]]
[1] "2013-01-01" "2013-02-01" "2013-03-01" "2013-04-01" "2013-05-01" "2013-06-01"

[[2]]
[1] "2013-01-01"

[[3]]
[1] "2013-01-01" "2013-02-01" "2013-03-01" "2013-04-01" "2013-05-01"

此时，我不知道如何创建最终表格。如果我尝试将此结果粘贴到我的表中，它会再次以数字形式转换日期

vf$sec1<-lapply(vf$sec, convFecha)

---

vf$sec1这不是一个完整的答案，而是使用
by
函数的第一步

out <- by(tbl, list(tbl$id_cliente), 
          function(x) seq(from=as.Date(min(x$fecha), , '%Y-%m-%d'), 
                          to=as.Date(max(x$fecha), '%Y-%m-%d'), by='month'))

> out 
: 1
[1] "2013-01-01" "2013-02-01" "2013-03-01" "2013-04-01" "2013-05-01"
[6] "2013-06-01"
------------------------------------------------------- 
: 2
[1] "2013-01-01"
------------------------------------------------------- 
: 3
[1] "2013-01-01" "2013-02-01" "2013-03-01" "2013-04-01" "2013-05-01"

out
: 1
[1] "2013-01-01" "2013-02-01" "2013-03-01" "2013-04-01" "2013-05-01"
[6] "2013-06-01"
------------------------------------------------------- 
: 2
[1] "2013-01-01"
------------------------------------------------------- 
: 3
[1] "2013-01-01" "2013-02-01" "2013-03-01" "2013-04-01" "2013-05-01"
这是我的尝试

tbl <- data.frame(id_cliente = c(1, 1, 1, 1, 2, 3, 3, 3), 
                  fecha = c('2013-01-01', '2013-06-01', '2013-05-01', '2013-04-01', 
                            '2013-01-01', '2013-01-01', '2013-05-01', '2013-04-01'))

ddply(tbl, .(id_cliente), function(d) {
    xMin <- min(as.Date(d$fecha))
    xMax <- max(as.Date(d$fecha))
    data.frame(fecha = format(seq(from=xMin, to=xMax, by='month'), format = "%d/%m/%Y"))
})

[[1]]
[1] "2013-01-01" "2013-02-01" "2013-03-01" "2013-04-01" "2013-05-01" "2013-06-01"

[[2]]
[1] "2013-01-01"

[[3]]
[1] "2013-01-01" "2013-02-01" "2013-03-01" "2013-04-01" "2013-05-01"

vf$sec1<-lapply(vf$sec, convFecha)

out <- by(tbl, list(tbl$id_cliente), 
          function(x) seq(from=as.Date(min(x$fecha), , '%Y-%m-%d'), 
                          to=as.Date(max(x$fecha), '%Y-%m-%d'), by='month'))

> out 
: 1
[1] "2013-01-01" "2013-02-01" "2013-03-01" "2013-04-01" "2013-05-01"
[6] "2013-06-01"
------------------------------------------------------- 
: 2
[1] "2013-01-01"
------------------------------------------------------- 
: 3
[1] "2013-01-01" "2013-02-01" "2013-03-01" "2013-04-01" "2013-05-01"

tbl <- data.frame(id_cliente = c(1, 1, 1, 1, 2, 3, 3, 3), 
                  fecha = c('2013-01-01', '2013-06-01', '2013-05-01', '2013-04-01', 
                            '2013-01-01', '2013-01-01', '2013-05-01', '2013-04-01'))

ddply(tbl, .(id_cliente), function(d) {
    xMin <- min(as.Date(d$fecha))
    xMax <- max(as.Date(d$fecha))
    data.frame(fecha = format(seq(from=xMin, to=xMax, by='month'), format = "%d/%m/%Y"))
})

   id_cliente      fecha
1           1 01/01/2013
2           1 01/02/2013
3           1 01/03/2013
4           1 01/04/2013
5           1 01/05/2013
6           1 01/06/2013
7           2 01/01/2013
8           3 01/01/2013
9           3 01/02/2013
10          3 01/03/2013
11          3 01/04/2013
12          3 01/05/2013