Unite multiple exclusion columns into single column

Each of the mark_*() functions appends a new column to the data. The unite_exclusions() function unites all of those columns in a single column that can be used to filter any or all exclusions downstream. Rows with multiple exclusions are concatenated with commas.

Usage

unite_exclusions(
  x,
  exclusion_types = c("duplicates", "duration", "ip", "location", "preview", "progress",
    "resolution"),
  separator = ",",
  remove = TRUE
)

Arguments

x

Data frame or tibble (preferably exported from Qualtrics).

exclusion_types

Vector of types of exclusions to unite.

separator

Character string specifying what character to use to separate multiple exclusion types

remove

Logical specifying whether to remove united columns (default = TRUE) or leave them in the data frame (FALSE)

Value

An object of the same type as x that includes the all of the same rows but with a single exclusion column replacing all of the specified exclusion_* columns.

Examples

# Unite all exclusion types
df <- qualtrics_text %>%
  mark_duplicates() %>%
  mark_duration(min_duration = 100) %>%
  mark_ip() %>%
  mark_location() %>%
  mark_preview() %>%
  mark_progress() %>%
  mark_resolution()
#> ℹ 2 NAs were found in IP addresses.
#> ℹ 7 out of 7 rows had duplicate IP addresses.
#> ℹ 1 NA was found in location.
#> ℹ 10 out of 10 rows had duplicate locations.
#> ℹ 4 out of 100 rows took less time than 100.
#> ℹ 2 out of 100 rows had NA values for IP addresses (check for preview data with 'check_preview()').
#> ℹ 14 out of 100 rows had IP address outside of US.
#> ℹ 1 out of 100 rows had no information on location.
#> ℹ 5 out of 100 rows were located outside of the US.
#> ℹ 2 rows were collected as previews. It is highly recommended to exclude these rows before further processing.
#> ℹ 6 out of 100 rows did not complete the study.
#> ℹ 3 out of 100 rows had screen resolutions less than 0 or height less than 0.
df2 <- df %>%
  unite_exclusions()

# Unite subset of exclusion types
df2 <- df %>%
  unite_exclusions(exclusion_types = c("duplicates", "duration", "ip"))