collapse (version 2.1.1)

fslice: Fast Slicing of Matrix-Like Objects

Description

A fast function to extract rows from a matrix or data frame-like object (by groups).

Usage

fslice(x, ..., n = 1, how = "first", order.by = NULL,
       na.rm = .op[["na.rm"]], sort = FALSE, with.ties = FALSE)
fslicev(x, cols = NULL, n = 1, how = "first", order.by = NULL,
        na.rm = .op[["na.rm"]], sort = FALSE, with.ties = FALSE, ...)

Value

A subset of x containing the selected rows.

Arguments

x

a matrix, data frame or list-like object, including 'grouped_df'.

...

for fslice: names or sequences of columns to group by - passed to fselect. If x is a matrix: atomic vectors to group x. Can be empty to operate on (un)grouped data. For fslicev: further arguments passed to GRP (such as decreasing, na.last, method).

cols

select columns to group by, using column names, indices, a logical vector or a selector function (e.g. is_categorical). It can also be a list of vectors, or, if x is a matrix, a single vector.

n

integer or proportion (if < 1). Number of rows to select from each group. If a proportion is provided, it is converted to the equivalent number of rows.

how

character. Method to select rows. One of:

• "first": select first n rows

• "last": select last n rows

• "min": select n rows with minimum values of order.by

• "max": select n rows with maximum values of order.by

order.by

vector or column name to order by when how is "min" or "max". Must be same length as rows in x. In fslice it must not be quoted.

na.rm

logical. If TRUE, missing values in order.by are removed before selecting rows.

sort

logical. If TRUE, sort selected rows on the grouping columns. FALSE uses first-appearance order (including grouping columns if how is "first" or "last") - fastest.

with.ties

logical. If TRUE and how is "min" or "max", returns all rows with the extreme value. Currently only supported for n = 1 and sort = FALSE.

See Also

fsubset, fcount, Data Frame Manipulation, Collapse Overview

Examples

# Basic usage
fslice(mtcars, n = 3)                    # First 3 rows
fslice(mtcars, n = 3, how = "last")      # Last 3 rows
fslice(mtcars, n = 0.1)                  # First 10% of rows

# Using order.by
fslice(mtcars, n = 3, how = "min", order.by = mpg)  # 3 cars with lowest mpg
fslice(mtcars, n = 3, how = "max", order.by = mpg)  # 3 cars with highest mpg

# With grouping
mtcars |> fslice(cyl, n = 2)                        # First 2 cars per cylinder
mtcars |> fslice(cyl, n = 2, sort = TRUE)           # with sorting (slightly less efficient)
mtcars |> fslice(cyl, n = 2, how = "min", order.by = mpg)  # 2 lowest mpg cars per cylinder

# Using with.ties
mtcars |> fslice(cyl, n = 1, how = "min", order.by = mpg, with.ties = TRUE)

# With grouped data
mtcars |>
  fgroup_by(cyl) |>
  fslice(n = 2, how = "max", order.by = mpg)        # 2 highest mpg cars per cylinder