How to create a new column with if condition - r

Question

This seems simple but I could not perform. Its different than sound similar question ask here.
I want to create new columns say df$col1, df$col2, df$col3 on dataframe df using if condition in the column already exists ie df$con and df$val.
I would like to write the value of column "val" in df$col1 if df$con > 3
I would like to write the value of col df$val in df$col2 if df$con<2
and I would like to write the 30% of df$val in df$col3 if df$con is between 1 and 3.
How should I do it ? Below is my dataframe df with two columns "con" for condition and "val" for value use.
dput(df)
structure(list(con = c(-33.09524956, -36.120924, -28.7020053,
-26.06385399, -18.45731163, -14.51817928, -20.1005132, -23.62346403,
-24.90464018, -23.51471516), val = c(0.016808197, 1.821442227,
4.078385886, 3.763593573, 2.617612605, 2.691796601, 1.060565469,
0.416400183, 0.348732675, 1.185505136)), .Names = c("con", "val"
), row.names = c(NA, 10L), class = "data.frame")

Answer 1

This might do it. First we write a function to change FALSE values to NA
foo <- function(x) {
is.na(x) <- x == FALSE
return(x)
}
Then apply it over the list of logical vectors and take the matching val column values
df[paste0("col", 1:3)] <- with(df, {
x <- list(con > 3, con < 2, con < 3 & con > 1)
lapply(x, function(y) val[foo(y)])
})
resulting in
df
con val col1 col2 col3
1 -33.09525 0.0168082 NA 0.0168082 NA
2 -36.12092 1.8214422 NA 1.8214422 NA
3 -28.70201 4.0783859 NA 4.0783859 NA
4 -26.06385 3.7635936 NA 3.7635936 NA
5 -18.45731 2.6176126 NA 2.6176126 NA
6 -14.51818 2.6917966 NA 2.6917966 NA
7 -20.10051 1.0605655 NA 1.0605655 NA
8 -23.62346 0.4164002 NA 0.4164002 NA
9 -24.90464 0.3487327 NA 0.3487327 NA
10 -23.51472 1.1855051 NA 1.1855051 NA

Answer 2

Could go the tidyverse way. The pipes %>% just send the output of each operation to the next function. mutate allows you to make a new column in your data frame, but you have to remember to store it at the top. It's stored as output. The ifelse allows you to conditionally assign values to your new column, for example the column col1. The second argument in ifelse is the output for a true condition, and the third argument is when ifelse is false. Hope this helps some too!
Go tidyverse!
library(tidyverse)
output <- df %>%
mutate(col1=ifelse(con>3, val, NA)) %>%
mutate(col2=ifelse(con<2, val, NA)) %>%
mutate(col3=ifelse(con<=3 & con>=1, 0.3*val, NA))
Here's a df that actually meets some of the conditions:
structure(list(con = c(-33.09524956, 2.5, -28.7020053, 2, -18.45731163,
2, -20.1005132, 6, -24.90464018, -23.51471516), val = c(0.016808197,
1.821442227, 4.078385886, 3.763593573, 2.617612605, 2.691796601,
1.060565469, 0.416400183, 0.348732675, 1.185505136)), .Names = c("con",
"val"), row.names = c(NA, 10L), class = "data.frame")
Here's the output after running the code:
con val col1 col2 col3
1 -33.09525 0.0168082 NA 0.0168082 NA
2 2.50000 1.8214422 NA NA 0.5464327
3 -28.70201 4.0783859 NA 4.0783859 NA
4 2.00000 3.7635936 NA NA 1.1290781
5 -18.45731 2.6176126 NA 2.6176126 NA
6 2.00000 2.6917966 NA NA 0.8075390
7 -20.10051 1.0605655 NA 1.0605655 NA
8 6.00000 0.4164002 0.4164002 NA NA
9 -24.90464 0.3487327 NA 0.3487327 NA
10 -23.51472 1.1855051 NA 1.1855051 NA