Erstellen von Tabellen in R

Vorbereitende Arbeiten

Pakete laden

library(sysfonts)
library(showtext)
library(palmerpenguins)
library(tidyverse)
library(knitr)
library(kableExtra)
library(gt)
library(DT)
library(reactable)
library(modelsummary)

Daten

Zur Demonstration wird das Paket «palmerpenguins» und der Datensatz «penguins» verwendet, welcher Angaben zu drei Pinguinarten enthält.

head(penguins)

# A tibble: 6 × 8
  species island    bill_length_mm bill_depth_mm flipper_length_mm body_mass_g
  <fct>   <fct>              <dbl>         <dbl>             <int>       <int>
1 Adelie  Torgersen           39.1          18.7               181        3750
2 Adelie  Torgersen           39.5          17.4               186        3800
3 Adelie  Torgersen           40.3          18                 195        3250
4 Adelie  Torgersen           NA            NA                  NA          NA
5 Adelie  Torgersen           36.7          19.3               193        3450
6 Adelie  Torgersen           39.3          20.6               190        3650
# ℹ 2 more variables: sex <fct>, year <int>

Tabelle mit kableExtra

kable(x = head(penguins), 
      format = "html", 
      caption = "Beispiel mit kableExtra") %>% 
  kable_styling(bootstrap_options = c("striped", "hover"))

Beispiel mit kableExtra

species	island	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex	year
Adelie	Torgersen	39.1	18.7	181	3750	male	2007
Adelie	Torgersen	39.5	17.4	186	3800	female	2007
Adelie	Torgersen	40.3	18.0	195	3250	female	2007
Adelie	Torgersen	NA	NA	NA	NA	NA	2007
Adelie	Torgersen	36.7	19.3	193	3450	female	2007
Adelie	Torgersen	39.3	20.6	190	3650	male	2007

Tabelle mit gt

gt(data = head(penguins), 
   locale = "de-CH") %>% 
  tab_header(title = "Pinguin-Daten", 
             subtitle = "Beispiel mit gt") %>% 
  fmt_number(columns = bill_length_mm:flipper_length_mm, 
             decimals = 1) %>% 
  fmt_number(columns = body_mass_g, 
             drop_trailing_zeros = TRUE, 
             sep_mark = "'")

Pinguin-Daten
Beispiel mit gt
species	island	bill_length_mm	bill_depth_mm	flipper_length_mm	body_mass_g	sex	year
Adelie	Torgersen	39.1	18.7	181.0	3’750	male	2007
Adelie	Torgersen	39.5	17.4	186.0	3’800	female	2007
Adelie	Torgersen	40.3	18.0	195.0	3’250	female	2007
Adelie	Torgersen	NA	NA	NA	NA	NA	2007
Adelie	Torgersen	36.7	19.3	193.0	3’450	female	2007
Adelie	Torgersen	39.3	20.6	190.0	3’650	male	2007

Tabelle mit DT

datatable(data = head(penguins), 
          options = list(autoWidth = TRUE, 
                         pageLength = 5, 
                         language = list(
                           url = "//cdn.datatables.net/plug-ins/1.10.11/i18n/German.json")
                         )
          )

Tabelle mit reactable

reactable(data = head(penguins), 
          resizable = TRUE, 
          searchable = TRUE, 
          defaultPageSize = 5, 
          highlight = TRUE, 
          striped = TRUE, 
          language = reactableLang(
            searchPlaceholder = "Suchen...", 
            pageNext = "Nächste", 
            pagePrevious = "Zurück", 
            pageInfo = "{rowStart}\u2013{rowEnd} von {rows} Zeilen")
          )

Tabelle mit modelsummary

model1 <- lm(formula = body_mass_g ~ flipper_length_mm, data = penguins)
model2 <- lm(formula = body_mass_g ~ flipper_length_mm + species, data = penguins)

modelsummary(models = list("Modell 1" = model1, 
                           "Modell 2" = model2), 
             output = "html")

	Modell 1	Modell 2
(Intercept)	−5780.831	−4031.477
	(305.815)	(584.151)
flipper_length_mm	49.686	40.705
	(1.518)	(3.071)
speciesChinstrap		−206.510
		(57.731)
speciesGentoo		266.810
		(95.264)
Num.Obs.	342	342
R2	0.759	0.783
R2 Adj.	0.758	0.781
AIC	5062.9	5031.5
BIC	5074.4	5050.7
Log.Lik.	−2528.427	−2510.762
F	1070.745	405.693
RMSE	393.12	373.33