pivot table in R - r

Question

I have date dataframe which like that
id weight beginning_date end_date age categ_car
22 2 1960-06-02 1960-06-02 17 A
17 4 2001-07-02 19 B
I want the following dataframe
id weight beginning_date end_date age categ_car
22 2 1960-06-02 1960-06-02 17 A
22 2 1961-06-02 1961-06-02 18 A
17 4 2001-07-02 19 B
17 4 2002-07-02 20 B
17 4 2003-07-02 21 B
17 4 2004-07-02 22 B
I know that I can use the melt function from the package reshape 2 to create the pivot but I don't how I can increment date and age?
thank you,
N

Answer 1

Here is some help to get you going. You need to get the year from date columns, apply the same function for date columns, and bind them all after:
library(data.table)
setDT(df)
AddWeightage<-function(a,x){
x<-cumsum(rep(1,x-1))
return(x+a)
}
cols<-c("age")
df[,lapply(.SD,AddWeightage,x=weight), by=.(categ_car),.SDcols=cols]
Here is the function to generate date columns:
AddWeightDate<-function(a,x){
x<-cumsum(rep(1,x-1))
a1<-x+year(a)
b<-substr(as.character(a),5,10)
return(sprintf('%s%s',a1,b))
}
cols<-c('beginning_date',"end_date")
df3<-df[,lapply(.SD,AddWeightDate,x=weight), by=.(categ_car),.SDcols=cols]

Answer 2

We can use complete and fill from tidyr package to find a solution. Important point is to generate a sequence of dates (increment by 1 year) using %m+% operator from lubridate package.
library(dplyr)
library(tidyr)
library(lubridate)
df %>%
mutate(beginning_date = ymd(beginning_date), end_date = ymd(end_date)) %>%
group_by(id) %>%
complete(beginning_date = seq(beginning_date, beginning_date %m+% years(weight-1),
by="1 year")) %>%
fill(weight, end_date, age, categ_car) %>%
arrange(desc(id)) %>%
select(id, weight, beginning_date, end_date, age, categ_car)
# # A tibble: 6 x 6
# # Groups: id [2]
# id weight beginning_date end_date age categ_car
# <int> <int> <date> <date> <int> <chr>
# 1 22 2 1960-06-02 1960-06-02 17 A
# 2 22 2 1961-06-02 1960-06-02 17 A
# 3 17 4 2001-07-02 NA 19 B
# 4 17 4 2002-07-02 NA 19 B
# 5 17 4 2003-07-02 NA 19 B
# 6 17 4 2004-07-02 NA 19 B
Update: Based on feedback from OP to handler multiple begining_date for same 'id`:
df %>%
mutate(beginning_date = ymd(beginning_date), end_date = ymd(end_date)) %>%
group_by(id) %>%
complete(beginning_date = seq(as.Date(min(beginning_date), origin="1970-01-01"),
as.Date(min(beginning_date), origin="1970-01-01") %m+% years(weight-1),
by="1 year")) %>%
fill(weight, end_date, age, categ_car) %>%
arrange(desc(id)) %>%
select(id, weight, beginning_date, end_date, age, categ_car)
Data
df <- read.table(text =
"id weight beginning_date end_date age categ_car
22 2 1960-06-02 1960-06-02 17 A
17 4 2001-07-02 NA 19 B",
header = TRUE, stringsAsFactors = FALSE)
Note: NA has been used instead of blank value for end_date.