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Accumulate over multiple columns horizontally with an R function

Source code

Description

This allows one to do rowwise operations, starting with an initial value (acc). See pl$reduce() to do rowwise operations without this initial value.

Usage

pl$fold(acc, lambda, exprs)

Arguments

acc an Expr or Into of the initial accumulator.
lambda R function which takes two polars Series as input and return one.
exprs Expressions to aggregate over. May also be a wildcard expression.

Value

An expression that will be applied rowwise

Examples

library(polars)

df = pl$DataFrame(mtcars)

# Make the row-wise sum of all columns
df$with_columns(
  pl$fold(
    acc = pl$lit(0),
    lambda = \(acc, x) acc + x,
    exprs = pl$col("*")
  )$alias("mpg_drat_sum_folded")
)
#> shape: (32, 12)
#> ┌──────┬─────┬───────┬───────┬───┬─────┬──────┬──────┬─────────────────────┐
#> │ mpg  ┆ cyl ┆ disp  ┆ hp    ┆ … ┆ am  ┆ gear ┆ carb ┆ mpg_drat_sum_folded │
#> │ ---  ┆ --- ┆ ---   ┆ ---   ┆   ┆ --- ┆ ---  ┆ ---  ┆ ---                 │
#> │ f64  ┆ f64 ┆ f64   ┆ f64   ┆   ┆ f64 ┆ f64  ┆ f64  ┆ f64                 │
#> ╞══════╪═════╪═══════╪═══════╪═══╪═════╪══════╪══════╪═════════════════════╡
#> │ 21.0 ┆ 6.0 ┆ 160.0 ┆ 110.0 ┆ … ┆ 1.0 ┆ 4.0  ┆ 4.0  ┆ 328.98              │
#> │ 21.0 ┆ 6.0 ┆ 160.0 ┆ 110.0 ┆ … ┆ 1.0 ┆ 4.0  ┆ 4.0  ┆ 329.795             │
#> │ 22.8 ┆ 4.0 ┆ 108.0 ┆ 93.0  ┆ … ┆ 1.0 ┆ 4.0  ┆ 1.0  ┆ 259.58              │
#> │ 21.4 ┆ 6.0 ┆ 258.0 ┆ 110.0 ┆ … ┆ 0.0 ┆ 3.0  ┆ 1.0  ┆ 426.135             │
#> │ 18.7 ┆ 8.0 ┆ 360.0 ┆ 175.0 ┆ … ┆ 0.0 ┆ 3.0  ┆ 2.0  ┆ 590.31              │
#> │ …    ┆ …   ┆ …     ┆ …     ┆ … ┆ …   ┆ …    ┆ …    ┆ …                   │
#> │ 30.4 ┆ 4.0 ┆ 95.1  ┆ 113.0 ┆ … ┆ 1.0 ┆ 5.0  ┆ 2.0  ┆ 273.683             │
#> │ 15.8 ┆ 8.0 ┆ 351.0 ┆ 264.0 ┆ … ┆ 1.0 ┆ 5.0  ┆ 4.0  ┆ 670.69              │
#> │ 19.7 ┆ 6.0 ┆ 145.0 ┆ 175.0 ┆ … ┆ 1.0 ┆ 5.0  ┆ 6.0  ┆ 379.59              │
#> │ 15.0 ┆ 8.0 ┆ 301.0 ┆ 335.0 ┆ … ┆ 1.0 ┆ 5.0  ┆ 8.0  ┆ 694.71              │
#> │ 21.4 ┆ 4.0 ┆ 121.0 ┆ 109.0 ┆ … ┆ 1.0 ┆ 4.0  ┆ 2.0  ┆ 288.89              │
#> └──────┴─────┴───────┴───────┴───┴─────┴──────┴──────┴─────────────────────┘