Concat polars objects

Description

Usage

pl$concat(
  ...,
  how = c("vertical", "vertical_relaxed", "horizontal", "diagonal", "diagonal_relaxed"),
  rechunk = TRUE,
  parallel = TRUE
)

Arguments

`…`	Either individual unpacked args or args wrapped in list(). Args can be eager as DataFrame, Series and R vectors, or lazy as LazyFrame and Expr. The first element determines the output of `$concat()`: if the first element is lazy, a LazyFrame is returned; otherwise, a DataFrame is returned (note that if the first element is eager, all other elements have to be eager to avoid implicit collect).
`how`	Bind direction. Can be "vertical" (like `rbind()`), "horizontal" (like `cbind()`), or "diagonal". For `“vertical”` and `“diagonal”`, adding the suffix `“\_relaxed”` will cast columns to their shared supertypes. For example, if we try to vertically concatenate two columns of types `i32` and `f64`, using `how = “vertical_relaxed”` will cast the column of type `i32` to `f64` beforehand.
`rechunk`	Perform a rechunk at last.
`parallel`	Only used for LazyFrames. If `TRUE` (default), lazy computations may be executed in parallel.

Details

Categorical columns/Series must have been constructed while global string cache enabled. See pl$enable_string_cache().

Value

DataFrame, Series, LazyFrame or Expr

Examples

library(polars)

# vertical
l_ver = lapply(1:10, function(i) {
  l_internal = list(
    a = 1:5,
    b = letters[1:5]
  )
  pl$DataFrame(l_internal)
})
pl$concat(l_ver, how = "vertical")

#> shape: (50, 2)
#> ┌─────┬─────┐
#> │ a   ┆ b   │
#> │ --- ┆ --- │
#> │ i32 ┆ str │
#> ╞═════╪═════╡
#> │ 1   ┆ a   │
#> │ 2   ┆ b   │
#> │ 3   ┆ c   │
#> │ 4   ┆ d   │
#> │ 5   ┆ e   │
#> │ …   ┆ …   │
#> │ 1   ┆ a   │
#> │ 2   ┆ b   │
#> │ 3   ┆ c   │
#> │ 4   ┆ d   │
#> │ 5   ┆ e   │
#> └─────┴─────┘

# horizontal
l_hor = lapply(1:10, function(i) {
  l_internal = list(
    1:5,
    letters[1:5]
  )
  names(l_internal) = paste0(c("a", "b"), i)
  pl$DataFrame(l_internal)
})
pl$concat(l_hor, how = "horizontal")

#> shape: (5, 20)
#> ┌─────┬─────┬─────┬─────┬───┬─────┬─────┬─────┬─────┐
#> │ a1  ┆ b1  ┆ a2  ┆ b2  ┆ … ┆ a9  ┆ b9  ┆ a10 ┆ b10 │
#> │ --- ┆ --- ┆ --- ┆ --- ┆   ┆ --- ┆ --- ┆ --- ┆ --- │
#> │ i32 ┆ str ┆ i32 ┆ str ┆   ┆ i32 ┆ str ┆ i32 ┆ str │
#> ╞═════╪═════╪═════╪═════╪═══╪═════╪═════╪═════╪═════╡
#> │ 1   ┆ a   ┆ 1   ┆ a   ┆ … ┆ 1   ┆ a   ┆ 1   ┆ a   │
#> │ 2   ┆ b   ┆ 2   ┆ b   ┆ … ┆ 2   ┆ b   ┆ 2   ┆ b   │
#> │ 3   ┆ c   ┆ 3   ┆ c   ┆ … ┆ 3   ┆ c   ┆ 3   ┆ c   │
#> │ 4   ┆ d   ┆ 4   ┆ d   ┆ … ┆ 4   ┆ d   ┆ 4   ┆ d   │
#> │ 5   ┆ e   ┆ 5   ┆ e   ┆ … ┆ 5   ┆ e   ┆ 5   ┆ e   │
#> └─────┴─────┴─────┴─────┴───┴─────┴─────┴─────┴─────┘

# diagonal
pl$concat(l_hor, how = "diagonal")

#> shape: (50, 20)
#> ┌──────┬──────┬──────┬──────┬───┬──────┬──────┬──────┬──────┐
#> │ a1   ┆ b1   ┆ a2   ┆ b2   ┆ … ┆ a9   ┆ b9   ┆ a10  ┆ b10  │
#> │ ---  ┆ ---  ┆ ---  ┆ ---  ┆   ┆ ---  ┆ ---  ┆ ---  ┆ ---  │
#> │ i32  ┆ str  ┆ i32  ┆ str  ┆   ┆ i32  ┆ str  ┆ i32  ┆ str  │
#> ╞══════╪══════╪══════╪══════╪═══╪══════╪══════╪══════╪══════╡
#> │ 1    ┆ a    ┆ null ┆ null ┆ … ┆ null ┆ null ┆ null ┆ null │
#> │ 2    ┆ b    ┆ null ┆ null ┆ … ┆ null ┆ null ┆ null ┆ null │
#> │ 3    ┆ c    ┆ null ┆ null ┆ … ┆ null ┆ null ┆ null ┆ null │
#> │ 4    ┆ d    ┆ null ┆ null ┆ … ┆ null ┆ null ┆ null ┆ null │
#> │ 5    ┆ e    ┆ null ┆ null ┆ … ┆ null ┆ null ┆ null ┆ null │
#> │ …    ┆ …    ┆ …    ┆ …    ┆ … ┆ …    ┆ …    ┆ …    ┆ …    │
#> │ null ┆ null ┆ null ┆ null ┆ … ┆ null ┆ null ┆ 1    ┆ a    │
#> │ null ┆ null ┆ null ┆ null ┆ … ┆ null ┆ null ┆ 2    ┆ b    │
#> │ null ┆ null ┆ null ┆ null ┆ … ┆ null ┆ null ┆ 3    ┆ c    │
#> │ null ┆ null ┆ null ┆ null ┆ … ┆ null ┆ null ┆ 4    ┆ d    │
#> │ null ┆ null ┆ null ┆ null ┆ … ┆ null ┆ null ┆ 5    ┆ e    │
#> └──────┴──────┴──────┴──────┴───┴──────┴──────┴──────┴──────┘

# if two columns don't share the same type, concat() will error unless we use
# `how = "vertical_relaxed"`:
test = pl$DataFrame(x = 1L) # i32
test2 = pl$DataFrame(x = 1.0) # f64

pl$concat(test, test2, how = "vertical_relaxed")

#> shape: (2, 1)
#> ┌─────┐
#> │ x   │
#> │ --- │
#> │ f64 │
#> ╞═════╡
#> │ 1.0 │
#> │ 1.0 │
#> └─────┘