find_missing_starts: Find start positions that cannot be found in ”data”

In groupdata2: Creating Groups from Data

Find start positions that cannot be found in `data`

Description

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Tells you which values and (optionally) skip-to-numbers that are recursively removed when using the "l_starts" method with `remove_missing_starts` set to TRUE.

Usage

find_missing_starts(data, n, starts_col = NULL, return_skip_numbers = TRUE)

Arguments

data	data.frame or vector. N.B. If `data` is a grouped data.frame, the function is applied group-wise and the output is a list of either vectors or lists. The names are based on the group indices (see dplyr::group_indices()).
n	List of starting positions. Skip values by c(value, skip_to_number) where skip_to_number is the nth appearance of the value in the vector. See group_factor() for explanations and examples of using the "l_starts" method.
starts_col	Name of column with values to match when `data` is a data.frame. Pass 'index' to use row names. (Character)
return_skip_numbers	Return skip-to-numbers along with values (Logical).

Value

List of start values and skip-to-numbers or a vector with the start values. Returns NULL if no values were found.

N.B. If `data` is a grouped data.frame, the function is applied group-wise and the output is a list of either vectors or lists. The names are based on the group indices (see dplyr::group_indices()).

Author(s)

Ludvig Renbo Olsen, [e-mail]

See Also

Other l_starts tools: differs_from_previous(), find_starts(), group_factor(), group()

Examples

# Attach packages
library(groupdata2)

# Create a data frame
df <- data.frame(
  "a" = c("a", "a", "b", "b", "c", "c"),
  stringsAsFactors = FALSE
)

# Create list of starts
starts <- c("a", "e", "b", "d", "c")

# Find missing starts with skip_to numbers
find_missing_starts(df, starts, starts_col = "a")

# Find missing starts without skip_to numbers
find_missing_starts(df, starts,
  starts_col = "a",
  return_skip_numbers = FALSE
)

groupdata2 documentation built on July 9, 2023, 6:46 p.m.