How to turn whole dataframe from string variables into numbers?

Question

I have a dataframe full of answers to a survey, so each column is filled with Never, Sometimes and Always and I need to change Never to the numeric 0, sometimes to the numeric 1 and always to the numeric 2. Is there a way to apply this change to the whole dataframe instead of individual columns?

Answer 1

Suppose your data frame looks like this:

df
#>           Q1        Q2        Q3
#> 1      Never    Always    Always
#> 2     Always     Never     Never
#> 3      Never     Never     Never
#> 4  Sometimes     Never     Never
#> 5      Never Sometimes     Never
#> 6     Always Sometimes Sometimes
#> 7     Always Sometimes     Never
#> 8  Sometimes Sometimes     Never
#> 9  Sometimes    Always Sometimes
#> 10    Always     Never Sometimes

Then you can do

df[] <- sapply(df, function(x) match(x, c("Never", "Sometimes", "Always")) - 1)

Which results in

df
#>    Q1 Q2 Q3
#> 1   0  2  2
#> 2   2  0  0
#> 3   0  0  0
#> 4   1  0  0
#> 5   0  1  0
#> 6   2  1  1
#> 7   2  1  0
#> 8   1  1  0
#> 9   1  2  1
#> 10  2  0  1

---

Reproducible data frame

set.seed(1)
df <- replicate(3, sample(c("Never", "Sometimes", "Always"), 10, TRUE))
df <- setNames(as.data.frame(df), c("Q1", "Q2", "Q3"))

Answer 2

Another approach could be using a named vector, probably more appropriate if you want more flexible in your translations.

set.seed(1)
df <- replicate(3, sample(c("Never", "Sometimes", "Always"), 10, TRUE))
df <- setNames(as.data.frame(df, stringsAsFactors = F), c("Q1", "Q2", "Q3"))

t <- c(0:2)
names(t) <- c("Never", "Sometimes", "Always")

as.data.frame(lapply(df, function(x) t[x]))

#    Q1 Q2 Q3
# 1   0  2  2
# 2   2  0  0
# 3   0  0  0
# 4   1  0  0
# 5   0  1  0
# 6   2  1  1
# 7   2  1  0
# 8   1  1  0
# 9   1  2  1
# 10  2  0  1