How to fill a column with random values in polars

I would like to know how to fill a column of a polars dataframe with random values. The idea is that I have a dataframe with a given number of columns, and I want to add a column to this dataframe which is filled with different random values (obtained from a random.random() function for example).

This is what I tried for now:

df = df.with_columns(
    pl.when((pl.col('Q') > 0)).then(random.random()).otherwise(pl.lit(1)).alias('Prob')
)

With this method, the result that I obtain is a column filled with one random value i.e. all the rows have the same value.

Is there a way to fill the column with different random values ?

Thanks by advance.

Solution

You need a "column" of random numbers the same height as your dataframe?

np.random.rand could be useful for this:

df = pl.DataFrame({"foo": [1, 2, 3]})

df.with_columns(pl.lit(np.random.rand(df.height)).alias("prob"))

shape: (3, 2)
┌─────┬──────────┐
│ foo ┆ prob     │
│ --- ┆ ---      │
│ i64 ┆ f64      │
╞═════╪══════════╡
│ 1   ┆ 0.657389 │
│ 2   ┆ 0.616265 │
│ 3   ┆ 0.142611 │
└─────┴──────────┘

df.with_columns(
   pl.when(pl.col("foo") > 2).then(pl.lit(np.random.rand(df.height)))
     .alias("prob")
)

shape: (3, 2)
┌─────┬──────────┐
│ foo ┆ prob     │
│ --- ┆ ---      │
│ i64 ┆ f64      │
╞═════╪══════════╡
│ 1   ┆ null     │
│ 2   ┆ null     │
│ 3   ┆ 0.686551 │
└─────┴──────────┘

It may also be possible to do similar with expressions?

e.g. with .int_range() and .sample()

df.with_columns(
   (pl.int_range(1000).sample(pl.len(), with_replacement=True) / 1000)
      .alias("prob")
)

shape: (3, 2)
┌─────┬───────┐
│ foo ┆ prob  │
│ --- ┆ ---   │
│ i64 ┆ f64   │
╞═════╪═══════╡
│ 1   ┆ 0.288 │
│ 2   ┆ 0.962 │
│ 3   ┆ 0.734 │
└─────┴───────┘