I have this example dataset
x <- c("hot", "cold", "warm", "hot", "hot")
y <- c("happy", "content", "happy", "sad", "annoyed")
df <- data.frame(x, y)
I want to find a quick way to convert the text to numbers, it doesn't matter which order the numbers are.
So the output would be:
x y
1 1
2 2
3 1
1 3
1 4
Many Thanks
With Base R:
df[] <- lapply(df, function(x) as.numeric(as.factor(x)))
df
#> x y
#> 1 2 3
#> 2 1 2
#> 3 3 3
#> 4 2 4
#> 5 2 1
With purrr:
library(purrr)
df %>% map(as.factor) %>% map_dfc(as.numeric)
#> # A tibble: 5 x 2
#> x y
#> <dbl> <dbl>
#> 1 2 3
#> 2 1 2
#> 3 3 3
#> 4 2 4
#> 5 2 1
Keep track of the labels with labelled:
df <- df %>% map(as.factor) %>% map_dfc(labelled::to_labelled)
df
#> # A tibble: 5 x 2
#> x y
#> <dbl+lbl> <dbl+lbl>
#> 1 2 [hot] 3 [happy]
#> 2 1 [cold] 2 [content]
#> 3 3 [warm] 3 [happy]
#> 4 2 [hot] 4 [sad]
#> 5 2 [hot] 1 [annoyed]
df$x
#> <labelled<double>[5]>
#> [1] 2 1 3 2 2
#>
#> Labels:
#> value label
#> 1 cold
#> 2 hot
#> 3 warm
Or keep the numbers next to the original values in a new column:
df[paste0(names(df), "_num")] <- lapply(df, function(x) as.numeric(as.factor(x)))
df
#> x y x_num y_num
#> 1 hot happy 2 3
#> 2 cold content 1 2
#> 3 warm happy 3 3
#> 4 hot sad 2 4
#> 5 hot annoyed 2 1
If you want to change only the character columns to numeric:
library(purrr)
df %>% map_if(is.character, as.factor) %>% map_dfc(as.numeric)
df %>% map_if(is.character, as.factor) %>% map_dfc(labelled::to_labelled)
Or choose them by name:
library(purrr)
cols <- c("x", "y")
df %>% map_at(cols, as.factor) %>% map_dfc(as.numeric)
df %>% map_at(cols, as.factor) %>% map_dfc(labelled::to_labelled)
df[paste0(cols, "_num")] <- lapply(df[cols], function(x) as.numeric(as.factor(x)))
Maybe try this with dplyr:
library(dplyr)
#Code
newdf <- df %>% mutate(across(everything(),~as.numeric(as.factor(.))))
Output:
x y
1 2 3
2 1 2
3 3 3
4 2 4
5 2 1
In order to see the values, you can try this:
#Code 2
newdf2 <- df %>% mutate(across(everything(),~as.factor(.))) %>%
mutate(across(everything(),.fns = list(value = ~ as.numeric(.))))
Output:
x y x_value y_value
1 hot happy 2 3
2 cold content 1 2
3 warm happy 3 3
4 hot sad 2 4
5 hot annoyed 2 1
If we add a numeric variable, this should work:
#Code 3
newdf <- df %>% mutate(across(x:y,~as.factor(.))) %>%
mutate(across(x:y,.fns = list(value = ~ as.numeric(.))))
Output:
x y number x_value y_value
1 hot happy 10 2 3
2 cold content 20 1 2
3 warm happy 30 3 3
4 hot sad 40 2 4
5 hot annoyed 50 2 1
You could use rapply:
rapply(type.convert(df), function(x)as.integer(factor(x, unique(x))),'factor',how = 'replace')
x y
1 1 1
2 2 2
3 3 1
4 1 3
5 1 4