R: fill new columns in data.frame based on row values by condition?

Question

I want to create a new columns in my data.frame, based on values in my rows.

If \'type\" is not equal to \"a\", my \"new.area\" columns should contain the data from \"ar

Answer 1

Here is a base R solution using index subsetting ([) and match:

my.df$new.area <- with(my.df, area[type == "a"][match(distance, distance[type == "a"])])

which returns

my.df
   distance area type new.area
1         1   11    a       11
2         2   12    a       12
3         3   13    a       13
4         4   14    a       14
5         5   15    a       15
6         1   16    b       11
7         2   17    b       12
8         3   18    b       13
9         4   19    b       14
10        5   20    b       15

area[type == "a"] supplies the vector of possibilities. match is used to return the indices from this vector through the distance variable. with is used to avoid the repeated use of my.df$.

Answer 2

We can use data.table

library(data.table)
setDT(my.df)[, new.area := area[type=="a"] , distance]
my.df
#     distance area type new.area
# 1:        1   11    a       11
# 2:        2   12    a       12
# 3:        3   13    a       13
# 4:        4   14    a       14
# 5:        5   15    a       15
# 6:        1   16    b       11
# 7:        2   17    b       12
# 8:        3   18    b       13
# 9:        4   19    b       14
#10:        5   20    b       15

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Or we can use the numeric index of distance as it is in a sequence

with(my.df, area[type=="a"][distance])
#[1] 11 12 13 14 15 11 12 13 14 15