Get formatted flextable of response rates for the Absolvent:innenbefragung

Usage

rub_table_ab(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
studienabschluss <- data.frame(
  stringsAsFactors = FALSE,
  studienabschluss = 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 Absolvent:innen / g\u00FCltige Frageb\u00F6gen",
                       "R\u00FCcklaufquote Absolvent:innenbefragungen"),
  koepfe_rub = c(NA,"9.887","9.969",NA,
                 "6.673","3.164","1.708","30","6.081","404","1.796",NA,
                 "4.611","882","4.778","265","3.614","5.086","620",
                 "19.856","35%"),
  koepfe_rub_perc = c(NA,"50%","50%",NA,"34%",
                      "16%","8,6%","0,2%","31%","2,0%","9,0%",NA,"23%",
                      "4,4%","24%","1,3%","18%","26%","3,1%","100%","35%"),
  koepfe_bef = c(NA,"3.594","3.358",NA,
                 "2.643","1.352","413","11","1.897","162","474",NA,
                 "1.724","186","1.603","108","1.544","1.613","174",
                 "6.952","35%"),
  koepfe_bef_perc = c(NA,"52%","48%",NA,"38%",
                      "19%","5,9%","0,2%","27%","2,3%","6,8%",NA,"25%",
                      "2,7%","23%","1,6%","22%","23%","2,5%","100%","35%"),
  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,
  col_keys = c(
    "studienabschluss","koepfe_rub","koepfe_rub_perc","koepfe_bef","koepfe_bef_perc"
  ),
  colC = c(
    "Studienabschluss","Absolventinnen und Absolventen (Pr\u00FCfungsjahrg\u00E4nge 2016 bis 2019)",
    "Absolventinnen und Absolventen (Pr\u00FCfungsjahrg\u00E4nge 2016 bis 2019)",
    "Absolventinnen und Absolventen (Pr\u00FCfungsjahrg\u00E4nge 2016 bis 2019)",
    "Absolventinnen und Absolventen (Pr\u00FCfungsjahrg\u00E4nge 2016 bis 2019)"
  ),
  colB = c(
    "Studienabschluss","Angeschrieben","Angeschrieben","G\u00FCltige Frageb\u00F6gen",
    "G\u00FCltige Frageb\u00F6gen"
  ),
  colA = c(
    "Studienabschluss","K\u00F6pfe","(in %)","K\u00F6pfe","(in %)"
  )
)

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

# Function call
rub_table_ab(
  df = studienabschluss,
  typolog = typology,
  headings = headings
)
#> a flextable object.
#> col_keys: `studienabschluss`, `koepfe_rub`, `koepfe_rub_perc`, `koepfe_bef`, `koepfe_bef_perc` 
#> header has 3 row(s) 
#> body has 21 row(s) 
#> original dataset sample: 
#>   studienabschluss koepfe_rub koepfe_rub_perc koepfe_bef koepfe_bef_perc row_id
#> 1       Geschlecht       <NA>            <NA>       <NA>            <NA>      1
#> 2         weiblich      9.887             50%      3.594             52%      2
#> 3         männlich      9.969             50%      3.358             48%      3
#> 4     Abschlussart       <NA>            <NA>       <NA>            <NA>      4
#> 5  Bachelor 1-Fach      6.673             34%      2.643             38%      5