Session Script T5, Advanced object types (April 6, 2022)

T5-SessionNotes

# Session Script T5, Advanced object types (April 6, 2022)

# Factors - Slide 10

f_1 <- factor(c(rep("F", 2), rep("M", 3), rep("D", 3)), 
              levels = c("D", "F", "M"))
f_1

f_2 <- factor(c(rep("F", 2), rep("M", 3), rep("D", 3)))
f_2

f_3 <- factor(c(rep("F", 2), rep("D", 3)))
f_3

f_4 <- factor(c(rep("F", 2), rep("M", 3)), 
              levels = c("D", "F", "M"))
f_4

f_5 <- factor(c(rep("F", 2), rep("M", 3), rep("D", 3)), 
              levels = c("D", "M"))
f_5

table(f_4)
table(f_5)

# Data frames and tibbles - slide 13

df_1 <- data.frame(
  "c1"= seq(1, 2, length.out=4),
  "c2" = seq(4, 5, length.out=4),
  "c3" = c(rep(TRUE, 2), rep(FALSE, 2))
)

tb_1 <- tibble::as_tibble(df_1)

# Quick exercises - slide 15

# Create a factor with the levels “still”, “medium” and “sparkling”, 
#  and arbitrary instances of the three levels

f1 <- factor(c(rep("still", 4),  rep("medium", 5), rep("sparkling", 3)))

# Get the relative frequencies for “medium” of this factor
# Häufigkeiten von allen Elementen
abs_freqs <- table(f1)
# Häufigkeiten teilen durch Anzahl an Elementen
n_elements <- length(f1)
# Compute relative freqs:
round(abs_freqs / n_elements * 100, 2)

# Create a data frame with two columns, one called “nb” containing the 
#  numbers 1 to 5 as double, the other called “char” containing the 
#  numbers 6 to 10 as character

# Create columns
nb_ <- seq(1, 5)
char_ <- as.character(seq(6, 10))

# Create data frame
df_s_a <- data.frame(
  "nb"=nb_, 
  "char"=char_
  )

df_s <- data.frame(
  "nb"=as.double(seq(1, 5)), 
  "char"=as.character(seq(6, 10))
)

# Transform this data frame into a tibble!
tb_s <- tibble::as_tibble(df_s)
tb_s

# Extract the second column of this tibble such that you have a vector
tb_s[["char"]]