Dynamically index a column in Polars

Question

I have a simple dataframe look like this:

import polars as pl

df = pl.DataFrame({ 
    'ref': ['a', 'b', 'c', 'd', 'e', 'f'], 
    'idx': [4, 3, 1, 6, 2, 5], 
})

How can I obtain the result as creating a new column as ref[idx], which is dynamic index from another column?

out = pl.DataFrame({     
    'ref': ['a', 'b', 'c', 'd', 'e', 'f'],     
    'idx': [4, 3, 1, 6, 2, 5],     
    'ref[idx]': ['d', 'c', 'a', 'f', 'b', 'e'], 
})

shape: (6, 3)
┌─────┬─────┬──────────┐
│ ref ┆ idx ┆ ref[idx] │
│ --- ┆ --- ┆ ---      │
│ str ┆ i64 ┆ str      │
╞═════╪═════╪══════════╡
│ a   ┆ 4   ┆ d        │
│ b   ┆ 3   ┆ c        │
│ c   ┆ 1   ┆ a        │
│ d   ┆ 6   ┆ f        │
│ e   ┆ 2   ┆ b        │
│ f   ┆ 5   ┆ e        │
└─────┴─────┴──────────┘

Answer 1

Polars has .get() / .gather() expressions for extracting values by index.

df.with_columns(
    pl.col("ref").get(pl.col("idx") - 1).alias("ref[idx]")
)

shape: (6, 3)
┌─────┬─────┬──────────┐
│ ref ┆ idx ┆ ref[idx] │
│ --- ┆ --- ┆ ---      │
│ str ┆ i64 ┆ str      │
╞═════╪═════╪══════════╡
│ a   ┆ 4   ┆ d        │
│ b   ┆ 3   ┆ c        │
│ c   ┆ 1   ┆ a        │
│ d   ┆ 6   ┆ f        │
│ e   ┆ 2   ┆ b        │
│ f   ┆ 5   ┆ e        │
└─────┴─────┴──────────┘