CODEWITHSUNDEEP
r
Chaitu
Chaitu

Reputation: 151

add a new columns based on the already available data

I have a data look's like this

df

    df = data.frame(
    id = c(1,1,1,1,1,2,2,2),
    value = c('a','b','c','d','e','a','b','c'))


    ------------
    id      value
    ------------
    1       a
    ------------
    1       b
    ------------
    1       c
    ------------
    1       d
    ------------
    1       e
    ------------
    2       a
    ------------
    2       b
    ------------
    2       c
    ------------

now I want to add a new column based on the value that should look like this

    ---------------------------
    id      value   from    to
    ---------------------------
    1       a       a       e
    ---------------------------
    1       b       a       e
    ---------------------------
    1       c       a       e
    ---------------------------
    1       d       a       e
    ---------------------------
    1       e       a       e
    ---------------------------
    2       a       a       c
    ---------------------------
    2       b       a       c
    ---------------------------
    2       c       a       c
    ---------------------------

I don't know if the answer is already available if it already available please provide me the link

Upvotes: 0

Views: 50

Answers (2)

Sotos
Sotos

Reputation: 51582

You can use ave, along with head (for first) and tail (for last) i.e.

df$from <- with(df, ave(value, id, FUN = function(i)head(i, 1)))

#and

df$to <- with(df, ave(value, id, FUN = function(i)tail(i, 1)))

Using data.table

library(data.table)

setDT(df)[, c('from', 'to') := list(data.table::first(value), data.table::last(value)), by = id][]

Upvotes: 3

tifu
tifu

Reputation: 1411

Another solution using dplyr:

library(dplyr)

df %>% 
group_by(id) %>%
mutate(from = first(value), to = last(value)) 

id  value     from   to
1      a      a      e
1      b      a      e
1      c      a      e
1      d      a      e
1      e      a      e
2      a      a      c
2      b      a      c
2      c      a      c

Upvotes: 2

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