Get formatted flextable of response rates for the Verlaufsbefragung

Usage

rub_table_vb(df, typology, headings, padding = 3L)

Arguments

df: Data frame
typology: Data frame with flextable typology
headings: Character vectors of headings
padding: Integer, padding in pts (points) passed to flextable::padding()

Value

Formatted Flextable

Illustrations

Examples

# Create example data
studienverlauf <- data.frame(
  stringsAsFactors = FALSE,
  studienverlauf = c("Geschlecht","weiblich",
                     "m\u00E4nnlich","Abschlussart","Bachelor 1-Fach",
                     "Bachelor 2-F\u00E4cher","Staatsexamen","Magister Theologiae",
                     "Master 1-Fach","Master 2-F\u00E4cher",
                     "Master of Education","F\u00E4chergruppe (erstes Studienfach)",
                     "Geisteswissenschaften",
                     "Humanmedizin / Gesundheitswissenschaften","Ingenieurwissenschaften",
                     "Kunst, Kunstwissenschaft","Mathematik, Naturwissenschaften",
                     "Rechts-, Wirtschafts-, Sozialwissenschaften","Sport",
                     "Gesamtzahl angeschriebene Studierende / g\u00FCltige Frageb\u00F6gen",
                     "R\u00FCcklaufquote Studienverlaufsbefragungen"),
  koepfe_2fs_rub = c(NA,"1.597","1.576",NA,
                     NA,NA,NA,NA,"2.590","99","484",NA,"733",NA,
                     "776","40","718","805","101","3.173","38%"),
  koepfe_2fs_rub_perc = c(NA,"50%","50%",NA,NA,
                          NA,NA,NA,"82%","3,1%","15%",NA,"23%",NA,
                          "24%","1,3%","23%","25%","3,2%","100%","38%"),
  koepfe_2fs_bef = c(NA,"652","561",NA,NA,
                     NA,NA,NA,"964","49","200",NA,"278",NA,"281",
                     "18","320","278","38","1.213","38%"),
  koepfe_2fs_bef_perc = c(NA,"54%","46%",NA,NA,
                          NA,NA,NA,"79%","4,0%","16%",NA,"23%",NA,
                          "23%","1,5%","26%","23%","3,1%","100%","38%"),
  koepfe_5fs_rub = c(NA,"5.720","5.785",NA,
                     "6.010","3.320","2.102","73",NA,NA,NA,NA,
                     "2.942","942","2.256","178","1.912","2.977","298",
                     "11.505","32%"),
  koepfe_5fs_rub_perc = c(NA,"50%","50%",NA,
                          "52%","29%","18%","0,6%",NA,NA,NA,NA,"26%",
                          "8,2%","20%","1,5%","17%","26%","2,6%","100%","32%"),
  koepfe_5fs_bef = c(NA,"2.111","1.548",NA,
                     "1.771","1.141","723","24",NA,NA,NA,NA,"934",
                     "332","638","49","661","966","79","3.659",
                     "32%"),
  koepfe_5fs_bef_perc = c(NA,"58%","42%",NA,
                          "48%","31%","20%","0,7%",NA,NA,NA,NA,"26%",
                          "9,1%","17%","1,3%","18%","26%","2,2%","100%","32%"),
  row_id = c(1L,2L,3L,4L,5L,6L,
             7L,8L,9L,10L,11L,12L,13L,14L,15L,16L,17L,18L,
             19L,20L,21L)
)

typology <- data.frame(
  stringsAsFactors = FALSE,
  NA,
  col_keys = c(
    "studienverlauf","koepfe_2fs_rub","koepfe_2fs_rub_perc","koepfe_2fs_bef",
    "koepfe_2fs_bef_perc","koepfe_5fs_rub","koepfe_5fs_rub_perc","koepfe_5fs_bef",
    "koepfe_5fs_bef_perc"
  ),
  colD = c(
    "Studienverlauf","Studierende (WiSe 18/19 bis  WiSe 20/21)",
    "Studierende (WiSe 18/19 bis  WiSe 20/21)","Studierende (WiSe 18/19 bis  WiSe 20/21)",
    "Studierende (WiSe 18/19 bis  WiSe 20/21)","Studierende (WiSe 18/19 bis  WiSe 20/21)",
    "Studierende (WiSe 18/19 bis  WiSe 20/21)","Studierende (WiSe 18/19 bis  WiSe 20/21)",
    "Studierende (WiSe 18/19 bis  WiSe 20/21)"
  ),
  colC = c(
    "Studienverlauf","2. Fachsemester","2. Fachsemester","2. Fachsemester","2. Fachsemester",
    "5. Fachsemester","5. Fachsemester","5. Fachsemester","5. Fachsemester"
  ),
  colB = c(
    "Studienverlauf","Angeschrieben","Angeschrieben","G\u00FCltige Frageb\u00F6gen",
    "G\u00FCltige Frageb\u00F6gen","Angeschrieben","Angeschrieben","G\u00FCltige Frageb\u00F6gen",
    "G\u00FCltige Frageb\u00F6gen"
  ),
  colA = c(
    "Studienverlauf","K\u00F6pfe","(in %)","K\u00F6pfe","(in %)","K\u00F6pfe","(in %)",
    "K\u00F6pfe","(in %)"
  )
)

headings <- c(
  "Geschlecht", "Abschlussart", "F\u00E4chergruppe (erstes Studienfach)",
  "Gesamtzahl angeschriebene Studierende / g\u00FCltige Frageb\u00F6gen",
  "R\u00FCcklaufquote Studienverlaufsbefragungen"
)

# Function call
rub_table_vb(
  df = studienverlauf,
  typolog = typology,
  headings = headings
)
#> a flextable object.
#> col_keys: `studienverlauf`, `koepfe_2fs_rub`, `koepfe_2fs_rub_perc`, `koepfe_2fs_bef`, `koepfe_2fs_bef_perc`, `koepfe_5fs_rub`, `koepfe_5fs_rub_perc`, `koepfe_5fs_bef`, `koepfe_5fs_bef_perc` 
#> header has 5 row(s) 
#> body has 21 row(s) 
#> original dataset sample: 
#>    studienverlauf koepfe_2fs_rub koepfe_2fs_rub_perc koepfe_2fs_bef
#> 1      Geschlecht           <NA>                <NA>           <NA>
#> 2        weiblich          1.597                 50%            652
#> 3        männlich          1.576                 50%            561
#> 4    Abschlussart           <NA>                <NA>           <NA>
#> 5 Bachelor 1-Fach           <NA>                <NA>           <NA>
#>   koepfe_2fs_bef_perc koepfe_5fs_rub koepfe_5fs_rub_perc koepfe_5fs_bef
#> 1                <NA>           <NA>                <NA>           <NA>
#> 2                 54%          5.720                 50%          2.111
#> 3                 46%          5.785                 50%          1.548
#> 4                <NA>           <NA>                <NA>           <NA>
#> 5                <NA>          6.010                 52%          1.771
#>   koepfe_5fs_bef_perc row_id
#> 1                <NA>      1
#> 2                 58%      2
#> 3                 42%      3
#> 4                <NA>      4
#> 5                 48%      5