sjmisc (version 2.5.0)

row_count: Count row or column indices

Description

row_count() mimics base R's rowSums(), with sums for a specific value indicated by count. Hence, it is equivalent to rowSums(x == count, na.rm = TRUE). However, this function is designed to work nicely within a pipe-workflow and allows select-helpers for selecting variables and the return value is always a tibble (with one variable).

col_count() does the same for columns. The return value is a data frame with one row (the column counts) and the same number of columns as x.

Usage

row_count(x, ..., count, var = "rowcount", append = FALSE)
col_count(x, ..., count, var = "colcount", append = FALSE)

Arguments

x

A vector or data frame.

...

Optional, unquoted names of variables that should be selected for further processing. Required, if x is a data frame (and no vector) and only selected variables from x should be processed. You may also use functions like : or dplyr's select_helpers. See 'Examples' or package-vignette.

count

The value for which the row or column sum should be computed. May be a numeric value, a character string (for factors or character vectors), NA, Inf or NULL to count missing or infinite values, or null-values.

var

Name of new the variable with the row or column counts.

append

Logical, if TRUE and x is a data frame, x including the new variables as additional columns is returned; if FALSE (the default), only the new variables are returned.

Value

For row_sumes(), a tibble with one variable: the sum of count appearing in each row of x; for col_count(), a tibble with one row and the same number of variables as in x: each variable holds the sum of count appearing in each variable of x. If append = TRUE, x including this variable will be returned.

Examples

# NOT RUN {
library(dplyr)
library(tibble)
dat <- tribble(
  ~c1, ~c2, ~c3, ~c4,
    1,   3,   1,   1,
    2,   2,   1,   1,
    3,   1,   2,   3,
    1,   2,   1,   2,
    3,  NA,   3,   1,
   NA,   3,  NA,   2
)

row_count(dat, count = 1)
row_count(dat, count = NA)
row_count(dat, c1:c3, count = 2, append = TRUE)

col_count(dat, count = 1)
col_count(dat, count = NA)
col_count(dat, c1:c3, count = 2, append = TRUE)

# }