bayes-rules-notes/R/ch2.R

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611 B
R

# install.packages("bayesrules")
library(bayesrules)
library(dplyr)
data(fake_news)
# make it a tibble for the sake printing
fake_news <- tibble::as_tibble(fake_news)
fake_news |> glimpse()
# proportion of each type of article
fake_news |>
group_by(type) |>
summarise(
n = n(),
prop = n / nrow(fake_news) # <- is there a NSE way
# of getting total rows of
# original DF?
)
# we can also do this with the tally function
fake_news|>
group_by(type) |>
tally() |>
mutate(prop = n / sum(n))