CODEWITHSUNDEEP
r
lukey
lukey

Reputation: 13

Using an if statements and creating new columns

So I want to transfer the entries from one column vector (age in my example) of a dataframe into a new column vector (experience, which i define as experience = age - years of school). So, I can work out the number of years in school via the age, there are three different bands, eg in my example people below the age of 26 were in school for 14 years (other bands can be seen in code below). To find experience I would just bring these together.

I ran the code below, but got loads of errors, confused prompt signs, entries about parynthesis I did not understand. And it just returned me a vector with all the entries being 'age-12', rather than the different bands I was hoping for (some age-10, others age-14).

if (df[,4] < 26){
   df[,4] - 14
} elseif (df[,4] < 53) {
    df[,4] - 12 
} else (df[,4] - 10)

Any help would be hugely appreciated!

Upvotes: 0

Views: 32

Answers (2)

Allan Cameron
Allan Cameron

Reputation: 173793

You could use cut plus some indexing to achieve this with a single line of code:

df$exp <- df$age - c(14, 12, 10)[as.numeric(cut(df$age, c(0, 25, 52, Inf)))]

Suppose your data looked like this:

set.seed(69)
df <- data.frame(age = sample(16:70, 10))
df
#>    age
#> 1   47
#> 2   32
#> 3   42
#> 4   17
#> 5   63
#> 6   55
#> 7   28
#> 8   54
#> 9   62
#> 10  66

Then if you did

df$exp <- df$age - c(14, 12, 10)[as.numeric(cut(df$age, c(0, 25, 52, Inf)))]

Then df would look like this:

df
#>    age exp
#> 1   47  35
#> 2   32  20
#> 3   42  30
#> 4   17   3
#> 5   63  53
#> 6   55  45
#> 7   28  16
#> 8   54  44
#> 9   62  52
#> 10  66  56

Created on 2020-11-10 by the reprex package (v0.3.0)

Upvotes: 0

stefan
stefan

Reputation: 123838

The issue is that if is not vectorized. Instead you could use ifelse or dplyr::case_when.

Using some random example data:

set.seed(42)

df <- data.frame(
  a = 1,
  b = 2,
  c = 3,
  d = sample(20:100, 5)
)
df[,4]
#> [1] 68 84 44 93 37

ifelse(df[,4] < 26, df[,4] - 14, ifelse(df[,4] < 53, df[,4] - 12, df[,4] - 10))
#> [1] 58 74 32 83 25

dplyr::case_when(
  df[,4] < 26 ~  df[,4] - 14,
  df[,4] < 53 ~  df[,4] - 12,
  TRUE ~ df[,4] - 10
)
#> [1] 58 74 32 83 25

Upvotes: 1

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