unheadr (version 0.4.0)

mash_colnames: Make many header rows into column names

Description

Make many header rows into column names

Usage

mash_colnames(
  df,
  n_name_rows,
  keep_names = TRUE,
  sliding_headers = FALSE,
  sep = "_"
)

Value

The original data frame, but with new column names and without the top n rows that held the broken up names.

Arguments

df

A data.frame or tibble object in which the names are broken up across the top n rows.

n_name_rows

Number of rows at the top of the data to be used to create the new variable (column) names. Must be >= 1.

keep_names

If TRUE, existing names will be included when building the new variable names. Defaults to TRUE.

sliding_headers

If TRUE, empty values in the first (topmost) header header row be filled column-wise. Defaults to FALSE. See details.

sep

Character string to separate the unified values (default is underscore).

Author

This function was originally contributed by Jarrett Byrnes through a GitHub issue.

Details

Tables are often shared with the column names broken up across the first few rows. This function takes the number of rows at the top of a table that hold the broken up names and whether or not to include the names, and mashes the values column-wise into a single string for each column. The keep_names argument can be helpful for tables we imported using a skip argument. If keep_names is set to FALSE, adjust the value of n_name_rows accordingly.

This function will throw a warning when possible NA values end up in the variable names. sliding_headers can be used for tables with ragged names in which not every column has a value in the very first row. In these cases attribution by adjacency is assumed, and when sliding_headers is set to TRUE the names in the topmost row are filled row-wise. This can be useful for tables reporting survey data or experimental designs in an untidy manner.

Examples

babies <-
  data.frame(
    stringsAsFactors = FALSE,
    Baby = c(NA, NA, "Angie", "Yean", "Pierre"),
    Age = c("in", "months", "11", "9", "7"),
    Weight = c("kg", NA, "2", "3", "4"),
    Ward = c(NA, NA, "A", "B", "C")
  )
# Including the object names
mash_colnames(babies, n_name_rows = 2, keep_names = TRUE)

babies_skip <-
  data.frame(
    stringsAsFactors = FALSE,
    X1 = c("Baby", NA, NA, "Jennie", "Yean", "Pierre"),
    X2 = c("Age", "in", "months", "11", "9", "7"),
    X3 = c("Hospital", NA, NA, "A", "B", "A")
  )
#' # Discarding the automatically-generated names (X1, X2, etc...)
mash_colnames(babies_skip, n_name_rows = 3, keep_names = FALSE)

fish_experiment <-
  data.frame(
    stringsAsFactors = FALSE,
    X1 = c("Sample", NA, "Pacific", "Atlantic", "Freshwater"),
    X2 = c("Larvae", "Control", "12", "11", "10"),
    X3 = c(NA, "Low Dose", "11", "12", "8"),
    X4 = c(NA, "High Dose", "8", "7", "9"),
    X5 = c("Adult", "Control", "13", "13", "8"),
    X6 = c(NA, "Low Dose", "13", "12", "7"),
    X7 = c(NA, "High Dose", "10", "10", "9")
  )
# Ragged names
mash_colnames(fish_experiment,
  n_name_rows = 2,
  keep_names = FALSE, sliding_headers = TRUE
)