intial

.lintr

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+linters: lintr::linters_with_defaults(
+    line_length_linter(120), 
+    commented_code_linter = NULL, 
+    trailing_whitespace_linter = NULL
+  )
+

R/ch2.R

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+# 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))
+

README.md

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+A set of notes and examples from reading through the book _Bayes Rules!_.