CODEWITHSUNDEEP
rdate
cutebunny
cutebunny

Reputation: 789

Conditional add years to existing date in R

I have a data frame. Here is a sample part.

Lines <- "Category    date
desktop     2017-12-25
tablet      2016-05-13
desktop     2018-06-01
desktop     2017-08-06
tablet      2015-12-31"
DF <- read.table(text = Lines, header = TRUE)
DF$date <- as.Date(DF$date)

There are more than 1000 rows in the data frame.

What I would like to do is: if the category is desktop, how can I add 2 years to the existing date? If the category is tablet, how can I add only 1 year to the existing date? Thank you for the help!

Upvotes: 1

Views: 2241

Answers (5)

Sam Firke
Sam Firke

Reputation: 23004

Or using only the lubridate package for its years() function:

library(lubridate)
DF$date[DF$Category == "desktop"] <- DF$date[DF$Category == "desktop"] + years(2)
DF$date[DF$Category == "tablet"] <- DF$date[DF$Category == "tablet"] + years(1)

> DF
  Category       date
1  desktop 2019-12-25
2   tablet 2017-05-13
3  desktop 2020-06-01
4  desktop 2019-08-06
5   tablet 2016-12-31

Upvotes: 1

G. Grothendieck
G. Grothendieck

Reputation: 269431

This does not use any packages. The input data frame is DF . The code converts the date column to "POSIXlt" class in the first line giving lt, increments the year component of lt in the second line and converts lt back to "Date" class in the third line. (Note that the second line could easily be modified if additional categories were to be implemented by simply adding on more terms.)

lt <- as.POSIXlt(DF$date)
lt$year <- lt$year + 2 * (DF$Category == "desktop") + (DF$Category == "laptop")
DF$date <- as.Date(lt)

giving:

  Category       date
1  desktop 2019-12-25
2   tablet 2016-05-13
3  desktop 2020-06-01
4  desktop 2019-08-06
5   tablet 2015-12-31

Upvotes: 2

Colonel Beauvel
Colonel Beauvel

Reputation: 31161

If you have big data.frames, you can do:

library(lubridate)
library(data.table)

addYear = function(date, nyear){year(date)=year(date)+nyear; date}

setDT(df)[,date:=as.Date(date)][
          Category=='desktop', date:=addYear(date,2)][
          Category=='tablet', date:=addYear(date,1)]

#   Category       date
#1:  desktop 2019-12-25
#2:   tablet 2017-05-13
#3:  desktop 2020-06-01
#4:  desktop 2019-08-06
#5:   tablet 2016-12-31

Upvotes: 2

tchakravarty
tchakravarty

Reputation: 10954

Use ifelse:

library(readr)
library(lubridate)
library(dplyr)

dfX = read_table("Category    date
desktop     2017-12-25
tablet      2016-05-13
desktop     2018-06-01
desktop     2017-08-06
tablet      2015-12-31",
                 col_types = list(col_character(), col_date()))


dfX %>%
  mutate(date_new = ifelse(Category == "desktop", date + dyears(2), 
                           ifelse(Category == "tablet", date + dyears(1), date)))

Upvotes: 1

bramtayl
bramtayl

Reputation: 4024

This might be best done through merging.

library(dplyr)
library(lubridate)

additions = 
  data_frame(Category = c("desktop", "tablet"), 
             interval = c(2, 1))

data %>%
  left_join(additions) %>%
  mutate(date = ymd(date),
         interval = interval %>% as.period("year"),
         next_date = date + interval )

Upvotes: 0

Related Questions