mariposa (version 0.7.3)

to_numeric: Convert Factors or Labelled Variables to Numeric

Description

Converts factor levels or labelled values to numeric. For factors, uses the underlying integer codes (or the numeric value of levels if they are numeric strings). For labelled variables, extracts the underlying numeric values.

Usage

to_numeric(
  data,
  ...,
  use_labels = TRUE,
  start_at = NULL,
  keep_labels = FALSE,
  use.labels = NULL,
  start.at = NULL,
  keep.labels = NULL
)

Value

The input with variables converted to numeric. For single vector input, returns a numeric vector.

Arguments

data

A data frame, tibble, or a single vector.

...

Optional: unquoted variable names (tidyselect supported). If empty, converts all factor columns.

use_labels

If TRUE (default), attempts to use the numeric value of factor levels (e.g., level "3" becomes 3). If FALSE, uses sequential integers (1, 2, 3, ...).

start_at

If not NULL, the lowest numeric value in the output starts at this number. Default: NULL (use original values).

keep_labels

If TRUE, the former factor levels are stored as value labels on the result. Default: FALSE.

use.labels, start.at, keep.labels

Defunct dot-case argument names, removed in mariposa 0.6.9. Calling the function with any of them is an error; use the snake_case equivalents instead. (The formals are retained only so that the old names error clearly instead of being swallowed by ....)

Details

This function handles three input types:

1. Numeric factors (levels like "1", "2", "3"): Extracts the numeric values from the level names.

2. Text factors (levels like "Male", "Female"): Converts to sequential integers by default; use use_labels = FALSE to force this behavior even for numeric-looking levels.

3. haven_labelled: Extracts the underlying numeric vector, stripping the labelled class.

See Also

to_label() for the reverse (numeric -> factor), to_labelled() for creating labelled vectors

Other labels: copy_labels(), drop_labels(), find_var(), set_na(), to_character(), to_label(), to_labelled(), unlabel(), val_labels(), var_label()

Examples

# Numeric factor levels -> numeric
x <- factor(c("1", "3", "5", "3"))
to_numeric(x)
# [1] 1 3 5 3

# Sequential integers
to_numeric(x, use_labels = FALSE)
# [1] 1 2 3 2

# Haven labelled -> plain numeric
to_numeric(survey_data$life_satisfaction)