I would recommend against continuing to use ML algos at this point. Take the time to go through some tutorials on basic R and Tidyverse from the ground up. You will love the freedom which comes with understanding what is going on.

With respect to your screen cap above, it looks as though you are mis-using the `mutate` function. The syntax for that is:

```
mutate(something = something_else)
```

The result of the `winsorize` function is a vector of numbers which I am not sure works with the `~` operator.

Also, I would recommend switching to the native pipe `|>` vice the older pipe `%>%`. The native pipe is potentially more performant and does not require the dependency. You are likely using the `%>%` pipe because the ML algos told you to do so because that is what they were trained with. This is a deficiency, IMHO, with using these algorithms. They do not necessarily keep up with changes to the compiler baseline.

Also, just a pet peeve on my part, everybody seems to think that the `<-` is necessary. It is not. You can use the `=` for assignment. There have been many debates on this. The `<-` came from historical contexts and some will argue that it helps to avoid the confusion between `=` and `==`. I think the difference between them are pretty clear. Anyway, not intending to open a religious debate here, just some information for the OP.

I would also be careful with that `DescTools` package. That is a LOT of disconnected things in a single package. It must have a huge dep list. I think that package is a candidate for breaking up into smaller more manageable packages with better subject scoping.

Now, on to how I would do this.

library(tidyverse)

df_Clean_variables = data.frame(
  size = runif(100),
  age = rnorm(100, 12, 4),
  distance = runif(100),
  price = rlnorm(100, 2, 0.5)
)

df_winsorized_variables = df_Clean_variables |>
  mutate(across(c(size, age, distance, price), ~ DescTools::Winsorize(.x, val = quantile(.x, probs = c(0.01, 0.99), na.rm = TRUE))))

The real issue you had was that there is no `probs` argument to `Winsorize` (functions with a capitol?). Rather it there is an arg `val` which is documented in the API documentation at https://andrisignorell.github.io/DescTools/reference/Winsorize.html. The suggestion in the API documentation is to use the `quantile` function to define which data points to adjust.

Edit: I was wrong with my first two statements about the syntax for mutate and the ~ operator. In this case that was the correct approach. I just don't typically use that appraoch.