Add `replace { }.by { }` API for multi-column replacement using AddDsl

Converting our "movies" example to the compiler plugin, I came across the following notation:

```kt
.split { title }.by {
listOf(
"""\s*\(\d{4}\)\s*$""".toRegex().replace(title, ""),
"\\d{4}".toRegex().findAll(title).lastOrNull()?.value?.toIntOrNull() ?: -1,
)
}.into("title", "year")
```

This creates the columns `title: DataColumn` and `year: DataColumn`. The problem with this `list` notation is that the compiler plugin cannot read the types easily. It can only see them as `Any`, because that's the type of the list.

I tried several alternatives, but they all boiled down to multiple steps:
- add `title2` and `year`, remove the old `title`, rename `title2` to `title`
- replace or convert the `title` column to a column group of `title`/`year`, ungroup it again
- use `split` and then `cast` or `requireColumn`

But all seem to be way too complicated for what we want here: simply replacing a column with two new ones.

A new API could look like:
```kt
df.replace { title }.by { // AddDsl
"title" from {
"""\s*\(\d{4}\)\s*$""".toRegex().replace(title, "")
}
"year" from {
"\\d{4}".toRegex().findAll(title).lastOrNull()?.value?.toIntOrNull() ?: -1
}
}
```

or more generally:
```kt
df.replace { name and firstName and age }.by {
"name" from {
"$firstName $name ($age)"
}
"welcomeMessage" from {
"Hi, $firstName!"
}
}
```
We could explore other notations or names, of course, but it would narrow down to:
- remove some columns
- add some new ones

in one operation

Start by reviewing the existing split and into operations and the AddDsl notation shown in the issue. Compare the proposed replace { }.by { } forms and determine a consistent API for removing selected columns and adding typed replacement columns in one operation. Done means the API design is settled and the multi-column replacement use cases are supported.

Written by the indexing model from the issue text.