Impute mode

[njtierney]

Description

implements imputing the mode

Related Issue

#213

Example

library(naniar)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
vec <- rnorm(10)

vec[sample(1:10, 3)] <- NA

impute_mode(vec)
#>  [1] -0.82831377  1.00094758  0.94702118  0.94702118  0.94702118  0.64740837
#>  [7]  1.79198464 -0.08941483  1.27700962 -0.21884888

dat <- tibble(
  num = rnorm(10),
  int = rpois(10, 5),
  fct = factor(LETTERS[1:10])
) %>%
  mutate(
    across(
      everything(),
      \(x) set_prop_miss(x, prop = 0.25)
    )
  )

dat
#> # A tibble: 10 × 3
#>        num   int fct  
#>      <dbl> <int> <fct>
#>  1 -0.321     NA A    
#>  2 NA          3 B    
#>  3 -0.200     NA C    
#>  4  3.34       3 D    
#>  5  0.807      4 E    
#>  6 -0.915      4 F    
#>  7 NA          3 <NA> 
#>  8  0.0148     7 <NA> 
#>  9 -0.374      5 I    
#> 10  0.0479     5 J

dat %>%
  nabular() %>%
  mutate(
    num = impute_mode(num)
  )
#> # A tibble: 10 × 6
#>        num   int fct   num_NA int_NA fct_NA
#>      <dbl> <int> <fct> <fct>  <fct>  <fct> 
#>  1 -0.321     NA A     !NA    NA     !NA   
#>  2 -0.183      3 B     NA     !NA    !NA   
#>  3 -0.200     NA C     !NA    NA     !NA   
#>  4  3.34       3 D     !NA    !NA    !NA   
#>  5  0.807      4 E     !NA    !NA    !NA   
#>  6 -0.915      4 F     !NA    !NA    !NA   
#>  7 -0.183      3 <NA>  NA     !NA    NA    
#>  8  0.0148     7 <NA>  !NA    !NA    NA    
#>  9 -0.374      5 I     !NA    !NA    !NA   
#> 10  0.0479     5 J     !NA    !NA    !NA

^{Created on 2023-04-10 with reprex v2.0.2}

Session info

sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#>  setting  value
#>  version  R version 4.2.3 (2023-03-15)
#>  os       macOS Ventura 13.2
#>  system   aarch64, darwin20
#>  ui       X11
#>  language (EN)
#>  collate  en_US.UTF-8
#>  ctype    en_US.UTF-8
#>  tz       Australia/Hobart
#>  date     2023-04-10
#>  pandoc   2.19.2 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/ (via rmarkdown)
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────
#>  package     * version    date (UTC) lib source
#>  cli           3.6.0      2023-01-09 [1] CRAN (R 4.2.0)
#>  colorspace    2.1-0      2023-01-23 [1] CRAN (R 4.2.0)
#>  digest        0.6.31     2022-12-11 [1] CRAN (R 4.2.0)
#>  dplyr       * 1.1.1      2023-03-22 [1] CRAN (R 4.2.0)
#>  evaluate      0.20       2023-01-17 [1] CRAN (R 4.2.0)
#>  fansi         1.0.4      2023-01-22 [1] CRAN (R 4.2.0)
#>  fastmap       1.1.0      2021-01-25 [1] CRAN (R 4.2.0)
#>  fs            1.6.1      2023-02-06 [1] CRAN (R 4.2.0)
#>  generics      0.1.3      2022-07-05 [1] CRAN (R 4.2.0)
#>  ggplot2       3.4.1      2023-02-10 [1] CRAN (R 4.2.0)
#>  glue          1.6.2      2022-02-24 [1] CRAN (R 4.2.0)
#>  gtable        0.3.1      2022-09-01 [1] CRAN (R 4.2.0)
#>  htmltools     0.5.4      2022-12-07 [1] CRAN (R 4.2.0)
#>  knitr         1.42       2023-01-25 [1] CRAN (R 4.2.0)
#>  lifecycle     1.0.3      2022-10-07 [1] CRAN (R 4.2.0)
#>  magrittr      2.0.3      2022-03-30 [1] CRAN (R 4.2.0)
#>  munsell       0.5.0      2018-06-12 [1] CRAN (R 4.2.0)
#>  naniar      * 1.0.0.9000 2023-04-10 [1] local
#>  pillar        1.8.1      2022-08-19 [1] CRAN (R 4.2.0)
#>  pkgconfig     2.0.3      2019-09-22 [1] CRAN (R 4.2.0)
#>  purrr         1.0.1      2023-01-10 [1] CRAN (R 4.2.0)
#>  R.cache       0.16.0     2022-07-21 [1] CRAN (R 4.2.0)
#>  R.methodsS3   1.8.2      2022-06-13 [1] CRAN (R 4.2.0)
#>  R.oo          1.25.0     2022-06-12 [1] CRAN (R 4.2.0)
#>  R.utils       2.12.2     2022-11-11 [1] CRAN (R 4.2.0)
#>  R6            2.5.1      2021-08-19 [1] CRAN (R 4.2.0)
#>  reprex        2.0.2      2022-08-17 [1] CRAN (R 4.2.0)
#>  rlang         1.1.0      2023-03-14 [1] CRAN (R 4.2.0)
#>  rmarkdown     2.20       2023-01-19 [1] CRAN (R 4.2.0)
#>  rstudioapi    0.14       2022-08-22 [1] CRAN (R 4.2.0)
#>  scales        1.2.1      2022-08-20 [1] CRAN (R 4.2.0)
#>  sessioninfo   1.2.2      2021-12-06 [1] CRAN (R 4.2.0)
#>  styler        1.9.0      2023-01-15 [1] CRAN (R 4.2.0)
#>  tibble        3.2.1      2023-03-20 [1] CRAN (R 4.2.0)
#>  tidyselect    1.2.0      2022-10-10 [1] CRAN (R 4.2.0)
#>  utf8          1.2.3      2023-01-31 [1] CRAN (R 4.2.0)
#>  vctrs         0.6.1      2023-03-22 [1] CRAN (R 4.2.0)
#>  visdat        0.6.0      2023-02-02 [1] local
#>  withr         2.5.0      2022-03-03 [1] CRAN (R 4.2.0)
#>  xfun          0.37       2023-01-31 [1] CRAN (R 4.2.0)
#>  yaml          2.3.7      2023-01-23 [1] CRAN (R 4.2.0)
#> 
#>  [1] /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/library
#> 
#> ──────────────────────────────────────────────────────────────────────────────

Tests

Yes

NEWS + DESCRIPTION

Yes

[njtierney]

library(naniar)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union
vec <- rnorm(10)

vec[sample(1:10, 3)] <- NA

impute_mode(vec)
#>  [1] -0.8667728 -1.3941443 -1.2821929 -1.1371585 -0.7508977 -1.0704500
#>  [7] -1.1450668 -1.1450668  1.1446806 -1.1450668

dat <- tibble(
  num = rnorm(10),
  int = as.integer(rpois(10, 5)),
  fct = factor(LETTERS[1:10])
) %>%
  mutate(
    across(
      everything(),
      \(x) set_prop_miss(x, prop = 0.25)
    )
  )

dat
#> # A tibble: 10 × 3
#>        num   int fct  
#>      <dbl> <int> <fct>
#>  1 NA          6 A    
#>  2 NA         NA B    
#>  3  0.364      7 C    
#>  4 -1.22       4 D    
#>  5  0.0346     3 <NA> 
#>  6  0.0860     5 F    
#>  7 -0.486      4 <NA> 
#>  8 -0.930      5 H    
#>  9  0.932     NA I    
#> 10 -0.946      5 J

dat %>%
  nabular() %>%
  mutate(
    num = impute_mode(num),
    int = impute_mode(int),
    fct = impute_mode(fct)
  )
#> # A tibble: 10 × 6
#>        num   int fct   num_NA int_NA fct_NA
#>      <dbl> <dbl> <fct> <fct>  <fct>  <fct> 
#>  1 -0.787      6 A     NA     !NA    !NA   
#>  2 -0.787      5 B     NA     NA     !NA   
#>  3  0.364      7 C     !NA    !NA    !NA   
#>  4 -1.22       4 D     !NA    !NA    !NA   
#>  5  0.0346     3 A     !NA    !NA    NA    
#>  6  0.0860     5 F     !NA    !NA    !NA   
#>  7 -0.486      4 A     !NA    !NA    NA    
#>  8 -0.930      5 H     !NA    !NA    !NA   
#>  9  0.932      5 I     !NA    NA     !NA   
#> 10 -0.946      5 J     !NA    !NA    !NA

^{Created on 2023-04-10 with reprex v2.0.2}

Session info

sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#>  setting  value
#>  version  R version 4.2.3 (2023-03-15)
#>  os       macOS Ventura 13.2
#>  system   aarch64, darwin20
#>  ui       X11
#>  language (EN)
#>  collate  en_US.UTF-8
#>  ctype    en_US.UTF-8
#>  tz       Australia/Hobart
#>  date     2023-04-10
#>  pandoc   2.19.2 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/ (via rmarkdown)
#> 
#> ─ Packages ───────────────────────────────────────────────────────────────────
#>  package     * version    date (UTC) lib source
#>  cli           3.6.0      2023-01-09 [1] CRAN (R 4.2.0)
#>  colorspace    2.1-0      2023-01-23 [1] CRAN (R 4.2.0)
#>  digest        0.6.31     2022-12-11 [1] CRAN (R 4.2.0)
#>  dplyr       * 1.1.1      2023-03-22 [1] CRAN (R 4.2.0)
#>  evaluate      0.20       2023-01-17 [1] CRAN (R 4.2.0)
#>  fansi         1.0.4      2023-01-22 [1] CRAN (R 4.2.0)
#>  fastmap       1.1.0      2021-01-25 [1] CRAN (R 4.2.0)
#>  fs            1.6.1      2023-02-06 [1] CRAN (R 4.2.0)
#>  generics      0.1.3      2022-07-05 [1] CRAN (R 4.2.0)
#>  ggplot2       3.4.1      2023-02-10 [1] CRAN (R 4.2.0)
#>  glue          1.6.2      2022-02-24 [1] CRAN (R 4.2.0)
#>  gtable        0.3.1      2022-09-01 [1] CRAN (R 4.2.0)
#>  htmltools     0.5.4      2022-12-07 [1] CRAN (R 4.2.0)
#>  knitr         1.42       2023-01-25 [1] CRAN (R 4.2.0)
#>  lifecycle     1.0.3      2022-10-07 [1] CRAN (R 4.2.0)
#>  magrittr      2.0.3      2022-03-30 [1] CRAN (R 4.2.0)
#>  munsell       0.5.0      2018-06-12 [1] CRAN (R 4.2.0)
#>  naniar      * 1.0.0.9000 2023-04-10 [1] local
#>  pillar        1.8.1      2022-08-19 [1] CRAN (R 4.2.0)
#>  pkgconfig     2.0.3      2019-09-22 [1] CRAN (R 4.2.0)
#>  purrr         1.0.1      2023-01-10 [1] CRAN (R 4.2.0)
#>  R.cache       0.16.0     2022-07-21 [1] CRAN (R 4.2.0)
#>  R.methodsS3   1.8.2      2022-06-13 [1] CRAN (R 4.2.0)
#>  R.oo          1.25.0     2022-06-12 [1] CRAN (R 4.2.0)
#>  R.utils       2.12.2     2022-11-11 [1] CRAN (R 4.2.0)
#>  R6            2.5.1      2021-08-19 [1] CRAN (R 4.2.0)
#>  reprex        2.0.2      2022-08-17 [1] CRAN (R 4.2.0)
#>  rlang         1.1.0      2023-03-14 [1] CRAN (R 4.2.0)
#>  rmarkdown     2.20       2023-01-19 [1] CRAN (R 4.2.0)
#>  rstudioapi    0.14       2022-08-22 [1] CRAN (R 4.2.0)
#>  scales        1.2.1      2022-08-20 [1] CRAN (R 4.2.0)
#>  sessioninfo   1.2.2      2021-12-06 [1] CRAN (R 4.2.0)
#>  styler        1.9.0      2023-01-15 [1] CRAN (R 4.2.0)
#>  tibble        3.2.1      2023-03-20 [1] CRAN (R 4.2.0)
#>  tidyselect    1.2.0      2022-10-10 [1] CRAN (R 4.2.0)
#>  utf8          1.2.3      2023-01-31 [1] CRAN (R 4.2.0)
#>  vctrs         0.6.1      2023-03-22 [1] CRAN (R 4.2.0)
#>  visdat        0.6.0      2023-02-02 [1] local
#>  withr         2.5.0      2022-03-03 [1] CRAN (R 4.2.0)
#>  xfun          0.37       2023-01-31 [1] CRAN (R 4.2.0)
#>  yaml          2.3.7      2023-01-23 [1] CRAN (R 4.2.0)
#> 
#>  [1] /Library/Frameworks/R.framework/Versions/4.2-arm64/Resources/library
#> 
#> ──────────────────────────────────────────────────────────────────────────────