I have a df as follows:

import polars as pl

data_frame = pl.from_repr("""
┌──────┬──────┬──────┬──────┐
│ col0 ┆ col1 ┆ col2 ┆ col3 │
│ ---  ┆ ---  ┆ ---  ┆ ---  │
│ i64  ┆ i64  ┆ i64  ┆ i64  │
╞══════╪══════╪══════╪══════╡
│ 1    ┆ 1    ┆ -1   ┆ 1    │
│ -1   ┆ 1    ┆ -1   ┆ -1   │
│ 1    ┆ 1    ┆ -1   ┆ -1   │
│ -1   ┆ 1    ┆ -1   ┆ 1    │
│ 1    ┆ 1    ┆ -1   ┆ 1    │
└──────┴──────┴──────┴──────┘
""")

I need to count 1 and -1 values over the rows.

Namely, I need a new df (or new columns in the old one):

shape: (5, 2)
┌─────┬─────┐
│ pos ┆ neg │
│ --- ┆ --- │
│ u32 ┆ u32 │
╞═════╪═════╡
│ 3   ┆ 1   │
│ 1   ┆ 3   │
│ 2   ┆ 2   │
│ 2   ┆ 2   │
│ 3   ┆ 1   │
└─────┴─────┘

I solved with an example from the user guide but I don't understand how it works:

data_frame.select(
    pl.fold(acc=pl.lit(0), function=lambda acc, x: acc + x, exprs=pl.col("*") > 0).alias("sum")
)

# shape: (5, 1)
# ┌─────┐
# │ pos │
# │ --- │
# │ i32 │
# ╞═════╡
# │ 3   │
# │ 1   │
# │ 2   │
# │ 2   │
# │ 3   │
# └─────┘