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The sss package makes it easy to read and parse survey
data in the sss (triple-s) file
format.
Read a survey file
Display the results.
dat %>% 
  as_tibble()
#> # A tibble: 3 × 17
#>   Q1      Q2_1  Q2_2  Q2_3  Q2_4  Q2_5  Q2_6  Q2_7  Q2_8  Q2_9 Q3    Q4_1  Q4_2 
#>   <chr>  <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr> <chr> <chr>
#> 1 Visit…     1     0     1     0     0     0     0     0     1 "Amu… Sher… "Oth…
#> 2 Visit…     0     1     0     0     0     0     0     0     0 "   … Nott…  <NA>
#> 3 Visit…     1     0     0     1     0     0     0     0     1 "\"M… Other "\"M…
#> # ℹ 4 more variables: Q5 <dbl>, Q6 <lgl>, Q7 <chr>, Q99 <dbl>And view the structure of the file. Note that some columns have
additional attributes with variable.labels and
lable.table, e.g. Q99:
str(dat)
#> 'data.frame':    3 obs. of  17 variables:
#>  $ Q1  : chr  "Visited before within the year" "Visited before that" "Visited before within the year"
#>  $ Q2_1: num  1 0 1
#>  $ Q2_2: num  0 1 0
#>  $ Q2_3: num  1 0 0
#>  $ Q2_4: num  0 0 1
#>  $ Q2_5: num  0 0 0
#>  $ Q2_6: num  0 0 0
#>  $ Q2_7: num  0 0 0
#>  $ Q2_8: num  0 0 0
#>  $ Q2_9: num  1 0 1
#>  $ Q3  : chr  "Amusement Park                " "                              " "\"Marco's\" Restaurant          "
#>  $ Q4_1: chr  "Sherwood Forest" "Nottingham Castle" "Other"
#>  $ Q4_2: chr  "Other" NA "\"Maid Marion\" Cafe"
#>  $ Q5  : num  12 999 58
#>  $ Q6  : logi  TRUE TRUE FALSE
#>  $ Q7  : chr  "Within 3 months" "More than 1 years time" NA
#>  $ Q99 : num  1.4 0.9 0.7
#>  - attr(*, "variable.labels")= chr [1:17] "Number of visits" "Attractions visited" "Attractions visited" "Attractions visited" ...
#>  - attr(*, "label.table")=List of 8
#>   ..$ 1 : Named chr [1:3] "1" "2" "3"
#>   .. ..- attr(*, "names")= chr [1:3] "First visit" "Visited before within the year" "Visited before that"
#>   ..$ 2 : Named chr [1:6] "1" "2" "3" "4" ...
#>   .. ..- attr(*, "names")= chr [1:6] "Sherwood Forest" "Nottingham Castle" "\"Friar Tuck\" Restaurant" "\"Maid Marion\" Cafe" ...
#>   ..$ 3 : Named chr NA
#>   .. ..- attr(*, "names")= chr NA
#>   ..$ 4 : Named chr [1:6] "1" "2" "3" "4" ...
#>   .. ..- attr(*, "names")= chr [1:6] "Sherwood Forest" "Nottingham Castle" "\"Friar Tuck\" Restaurant" "\"Maid Marion\" Cafe" ...
#>   ..$ 5 : Named chr [1:2] "500" "999"
#>   .. ..- attr(*, "names")= chr [1:2] "500 or more" "Not stated"
#>   ..$ 6 : Named chr NA
#>   .. ..- attr(*, "names")= chr NA
#>   ..$ 7 : Named chr [1:3] "1" "2" "3"
#>   .. ..- attr(*, "names")= chr [1:3] "Within 3 months" "Between 3 months and 1 year" "More than 1 years time"
#>   ..$ 99: Named chr NA
#>   .. ..- attr(*, "names")= chr NAExtract the variable labels:
attr(dat, "variable.labels")
#>  [1] "Number of visits"                  "Attractions visited"              
#>  [3] "Attractions visited"               "Attractions visited"              
#>  [5] "Attractions visited"               "Attractions visited"              
#>  [7] "Attractions visited"               "Attractions visited"              
#>  [9] "Attractions visited"               "Attractions visited"              
#> [11] "Other attractions visited"         "Two favourite attractions visited"
#> [13] "Two favourite attractions visited" "Miles travelled"                  
#> [15] "Would come again"                  "When is that most likely to be"   
#> [17] "Case weight"And the label table for question 2:
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.