Как заменить значения метками в data.frames из spss файлов?

Question

Мне нужно прочитать сохраненный файл. Я использую пакет haven

library(haven)
dataset<- read_sav("datafile.sav")

В консоли я вижу метки:

        dput(head(voyages$portdep))
        structure(c(50422, 50299, 50299, 50299, NA, NA), label = "Port of departure", labels = c(Alicante = 10101, 
        Barcelona = 10102, Bilbao = 10103, Cadiz = 10104, Figuera = 10105, 
        Gibraltar = 10106, `La Coruña` = 10107, Santander = 10110, Seville = 10111, 
        `San Lucar` = 10112, Vigo = 10113, `Spain, port unspecified` = 10199, 
        Lagos = 10202, Lisbon = 10203, Oporto = 10204, `Ilho do Fayal` = 10205, 
        Setubal = 10206, `Portugal, port unspecified` = 10299, `Great Britain, port unspecified` = 10399, 
        Barmouth = 10401, Bideford = 10402, Birkenhead = 10403, Bristol = 10404, 
        Brixham = 10405, Broadstairs = 10406, Cawsand = 10407, Chepstow = 10408, 
        Chester = 10409, Colchester = 10410, Cowes = 10411, Dartmouth = 10412, 
        Deptford = 10413, Dover = 10414, Exeter = 10415, Folkstone = 10416, 
        Frodsham = 10417, Gainsborough = 10418, Greenwich = 10419, Guernsey = 10420, 
        Harwich = 10421, Hull = 10422, Ilfracombe = 10423, Ipswich = 10424, 
        `Isle of Man` = 10425, `Isle of Wight` = 10426, Jersey = 10427, 
        Kendal = 10428, `King's Lynn` = 10429, Lancaster = 10430, Lindale = 10431, 
        Liverpool = 10432, London = 10433, Lyme = 10434, Maryport = 10436, 
        `Milford Haven` = 10437, `New Shoreham` = 10438, `Newcastle upon Tyne` = 10439, 
        Newnham = 10440, `North Shields` = 10441, Norwich = 10443, Padstowe = 10444, 
        Parkgate = 10445, `Piel of Foulney` = 10446, Plymouth = 10447, 
        Poole = 10448, Portsery = 10449, Portsmouth = 10450, Poulton = 10451, 
        Preston = 10452, Ramsgate = 10453, Ravenglass = 10454, `River Thames` = 10455, 
        Rochester = 10456, Rotherhithe = 10457, Rye = 10458, Scarborough = 10459, 
        Sheerness = 10460, Shields = 10461, Shoreham = 10462, Sidmouth = 10463, 
        Southampton = 10464, Stockton = 10466, Stockwithe = 10467, Sunderland = 10468, 
        Teignmouth = 10469, Topsham = 10470, Torbay = 10471, Wales = 10472, 

В таблице html у меня есть только значения:

Как заменить значения метками в данных .frames из spss файлов? для отображения в html таблице?

с помощью пакета sjlabelled, я могу получить метки любого столбца:

library(sjlabelled)
get_labels(voyages$portdep)

1] "Аликанте" "Барселона" " Бильбао "" Кадис "
[5]" Фигуера "" Гибралтар "" Ла-Корунья "" Сантандер "
[9]" Севилья "" Сан-Лукар "" Vi go "" Испания, порт не указан »
[13] "Лагос", "Лиссабон", "Порту", "Ильхо до Фаял"
[17] "Сетубал", "Португалия, порт не указан" "Великобритания, порт не указан" "Бармут"
[21] "Bideford" "Birkenhead" "Bristol" "Brixham"
[25] "Broadstairs" "Cawsand" "Chepstow" "Chester"
[29] "Colchester" "Cowes" "Дартмут" "Deptford"
[33] «Довер», «Эксетер», «Фолкстон», «Фродшам»
[37], «Гейнсборо», «Гр». eenwich "" Гернси "" Harwich "
[41]" Корпус "" Ilfracombe "" Ипсвич "" Остров Мэн "
[45]" Остров Уайт "" Джерси "" Кендал "" Кингс Линн "

Я пытался:

В одном столбце:

  dataset2 <- dataset %>% mutate(portdep = get_labels(portdep))

Ошибка: столбец portdep должен иметь длину 36002 (количество строк) или один, а не 847

На всех фреймах данных:

  dataset2 <-  dataset %>% mutate_all(funs(get_labels(.)))

С той же ошибкой в ​​первом столбце: столбец xxx должен иметь длину 36002 (количество строк) или один, а не 2

Answer 1

Я думаю, вы можете получить то, что ищете, используя haven::as_factor.

Работает ли это?

library(haven)
library(dplyr)

dataset %>% 
  mutate_all(as_factor) %>%
  head() %>%
  View()

Answer 2

Вместо использования пакета haven, вы можете попробовать foreign. Я использовал свои собственные данные try.sav, включая переменную gender:

library(haven)
df_haven<- read_sav("try.sav")
class(df_haven$gender)
#> [1] "haven_labelled"
table(df_haven$gender)
#> 
#>    1    2 
#> 1972 2417
df_haven$gender
#> <Labelled double>: Gender
#>    [1] 2 2 2 1 2 2 2 2 2 2 2 2 2 1 2 2 2 2 2 1 2 2 2 2 2 2 1 1 1 1 2 2 2 2 2 2 2
#>   [38] 2 2 2 1 2 2 1 2 2 2 2 2 2 2 2 1 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
#>   [75] 2 2 1 1 2 2 1 2 1 2 1 1 2 1 2 1 1 2 2 2 2 2 1 1 2 2 1 2 1 2 2 2 1 1 2 2 1
#> ...
#> Labels:
#>  value  label
#>      1   male
#>      2 female

library(foreign)
df_foreign<- read.spss("try.sav", to.data.frame = TRUE) 
#> re-encoding from UTF-8
class(df_foreign$gender)
#> [1] "factor"
table(df_foreign$gender)
#> 
#>   male female 
#>   1972   2417
df_foreign$gender
#>    [1] female female female male   female female female female female female
#>   [11] female female female male   female female female female female male  
#>   [21] female female female female female female male   male   male   male  
#>   [31] female female female female female female female female female female
#>   [41] male   female female male   female female female female female female
#>   [51] female female male   female female female female male   female female
#>   [61] female female female female female female female female female female
#>   [71] female female female female female female male   male   female female
#>   [81] male   female male   female male   male   female male   female male  
#>   [91] male   female female female female female male   male   female female
....
#> Levels: male female

^{, созданную в 2020-01-06 пакетом Представления (v0.3.0)}