R Notebook

Cherokee VOT Across Years

  
library(ggplot2)
charokeeVOT <- read.delim("C:/Users/melan/Downloads/cherokeeVOT.txt")
View(charokeeVOT)
ggplot(charokeeVOT) +
  geom_col(aes(x= year, y= VOT))

This script loads a dataset containing VOT measurements for Cherokee speech and visualizes the data using R. After importing the dataset, a bar plot is generated with year on the x-axis and VOT on the y-axis. Each bar represents the VOT value associated with a given year, allowing for a visual comparison of VOT measurements across time.

Letter Frequency in Wordle Answer Words

library(tidyverse)
words <- read.csv("C:/Users/melan/Downloads/FreqWords.csv")

letters_df <- words %>%
  mutate(
    letter1 = str_sub(FreqWords, 1, 1),
    letter2 = str_sub(FreqWords, 2, 2),
    letter3 = str_sub(FreqWords, 3, 3),
    letter4 = str_sub(FreqWords, 4, 4),
    letter5 = str_sub(FreqWords, 5, 5)
  )
long <- letters_df %>%
  pivot_longer(cols = starts_with("letter"),
               names_to = "position",
               values_to = "character")

is.vector(str_split(words, ""))

[1] TRUE

ggplot(long, aes(x = character)) +
  geom_bar()

  labs(
    title = "Letter Frequency in Wordle Answers",
    x = "Letter",
    y = "Frequency"
  ) +
  theme_minimal()

NULL

This analysis investigates which letters occur most frequently in Wordle answer words. The dataset consists of a list of five-letter English words, with each word treated as a single observation. Using R, each word is split into its individual letters, and the data are reshaped so that each letter appears as its own row. The frequency of each letter is then calculated by counting how often it occurs across the entire Wordle answer list. These frequencies are visualized in a bar chart, making it easy to compare how commonly different letters appear in Wordle answers.