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114 lines
2.5 KiB
Markdown
114 lines
2.5 KiB
Markdown
# Convert labelled vectors to factors while preserving attributes
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This extends
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[as_factor](https://forcats.tidyverse.org/reference/as_factor.html) as
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well as
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[as_factor](https://forcats.tidyverse.org/reference/as_factor.html), by
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appending original attributes except for "class" after converting to
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factor to avoid ta loss in case of rich formatted and labelled data.
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## Usage
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``` r
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as_factor(x, ...)
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# S3 method for class 'factor'
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as_factor(x, ...)
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# S3 method for class 'logical'
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as_factor(x, ...)
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# S3 method for class 'numeric'
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as_factor(x, ...)
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# S3 method for class 'character'
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as_factor(x, ...)
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# S3 method for class 'haven_labelled'
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as_factor(
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x,
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levels = c("default", "labels", "values", "both"),
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ordered = FALSE,
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...
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)
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# S3 method for class 'labelled'
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as_factor(
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x,
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levels = c("default", "labels", "values", "both"),
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ordered = FALSE,
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...
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)
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# S3 method for class 'data.frame'
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as_factor(x, ..., only_labelled = TRUE)
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```
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## Arguments
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- x:
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Object to coerce to a factor.
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- ...:
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Other arguments passed down to method.
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- levels:
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How to create the levels of the generated factor:
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\* "default": uses labels where available, otherwise the values.
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Labels are sorted by value. \* "both": like "default", but pastes
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together the level and value \* "label": use only the labels;
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unlabelled values become \`NA\` \* "values": use only the values
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- ordered:
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If \`TRUE\` create an ordered (ordinal) factor, if \`FALSE\` (the
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default) create a regular (nominal) factor.
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- only_labelled:
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Only apply to labelled columns?
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## Details
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Please refer to parent functions for extended documentation. To avoid
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redundancy calls and errors, functions are copy-pasted here
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Empty variables with empty levels attribute are interpreted as logicals
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## Examples
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``` r
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# will preserve all attributes
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c(1, 4, 3, "A", 7, 8, 1) |> as_factor()
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#> [1] 1 4 3 A 7 8 1
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#> Levels: 1 4 3 A 7 8
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structure(c(1, 2, 3, 2, 10, 9),
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labels = c(Unknown = 9, Refused = 10)
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) |>
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as_factor() |>
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dput()
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#> structure(c(1L, 2L, 3L, 2L, 5L, 4L), levels = c("1", "2", "3",
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#> "9", "10"), class = "factor", labels = c(Unknown = 9, Refused = 10
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#> ))
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structure(c(1, 2, 3, 2, 10, 9),
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labels = c(Unknown = 9, Refused = 10),
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class = "haven_labelled"
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) |>
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as_factor() |> class()
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#> [1] "factor"
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structure(rep(NA,10),
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class = c("labelled")
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) |>
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as_factor() |> summary()
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#> FALSE TRUE NA's
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#> 0 0 10
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rep(NA,10) |> as_factor()
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#> [1] <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA> <NA>
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#> Levels: FALSE TRUE
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```
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