sparse_mean: Calculate mean from sparse vectors

In sparsevctrs: Sparse Vectors for Use in Data Frames

Calculate mean from sparse vectors

Description

Calculate mean from sparse vectors

Usage

sparse_mean(x, wts = NULL, na_rm = FALSE)

Arguments

x	A sparse numeric vector.
wts	A numeric vector, should be same length as x.
na_rm	Logical, whether to remove missing values. Defaults to FALSE.

Details

This function, as with any of the other helper functions assumes that the input x is a sparse numeric vector. This is done for performance reasons, and it is thus the users responsibility to perform input checking.

When wts is supplied, the weights are multiplied into x and the result is divided by the sum of the weights. With na_rm = TRUE, weights at positions where the weighted value is missing are dropped from the sum of the weights, so a missing weight removes that observation instead of returning NA as stats::weighted.mean() does.

Value

single numeric value.

Examples

sparse_mean(
  sparse_double(1000, 1, 1000)
)

sparse_mean(
  sparse_double(1000, 1, 1000, default = 1)
)

sparse_mean(
  sparse_double(c(10, 50, 11), c(1, 50, 111), 1000)
)

sparse_mean(
  sparse_double(c(10, NA, 11), c(1, 50, 111), 1000)
)

sparse_mean(
  sparse_double(c(10, NA, 11), c(1, 50, 111), 1000),
  na_rm = TRUE
)

sparsevctrs documentation built on Nov. 2, 2026, 1:09 a.m.