Count Occurrences of a Value Across Columns

Counts how often a specific value appears in each row across the selected variables. Useful for data quality checks (e.g., "How many items did a respondent answer with -9?") or for creating count-based indices.

Usage

row_count(data, ..., count, na.rm = TRUE)

Arguments

data

Your survey data (a data frame or tibble).

...

The variables to check. Supports tidyselect.

count

The value(s) to count: one value (count = 5) or a set (count = c(4, 5) counts cells equal to 4 or 5, like SPSS's COUNT n = v1 TO v5 (4, 5)). NA counts missing values (SPSS keyword MISSING). Missing codes of imported data (e.g. -9 read by read_spss() as a tagged NA) are counted when listed, as SPSS's COUNT counts user-missing values.

na.rm

If TRUE (default), NA values are ignored. If FALSE, any row containing a missing value that is not counted returns NA.

Value

An integer vector with one value per row — the count of how often count appears.

See also

row_sums() for row-wise sums, row_means() for row-wise means

Other scale: efa(), pomps(), reliability(), row_means(), row_sums()

Examples

library(dplyr)
data(survey_data)

# How many items did each respondent answer with the highest value (5)?
survey_data <- survey_data %>%
  mutate(n_top = row_count(., trust_government, trust_media,
                           trust_science, count = 5))

# Top-2 box (4 or 5) and number of missing answers per respondent
survey_data <- survey_data %>%
  mutate(n_top2 = row_count(., trust_government, trust_media,
                            trust_science, count = c(4, 5)),
         n_miss = row_count(., trust_government, trust_media,
                            trust_science, count = NA))