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library(tidyverse)

Load data

df <- read.csv(“data.csv”)

Create a column with the first letter of each name

df$first_letter <- substr(df$name, 1, 1)

Create a pivot table that counts the number of names that start with each letter

counts <- df %>%
count(first_letter) %>%
arrange(desc(n))

Print the results

print(counts)

1. **Load necessary libraries**: The code starts by loading the `tidyverse` library, which provides a collection of powerful data manipulation functions and tools.

2. **Load data from a CSV file**: It reads a CSV file named "data.csv" into a data frame called `df`. This data frame likely contains a column for names.

3. **Create a new column**: The code creates a new column called `first_letter` in the `df` data frame. This column extracts the first letter of each name in the `name` column using the `substr()` function.

4. **Count names starting with each letter**: Using the `count()` function, the code counts how many names start with each unique letter in the `first_letter` column. The results are stored in a new data frame called `counts`.

5. **Sort results**: The `arrange()` function is applied to the `counts` data frame to sort the results in descending order of the counts. This arranges the letters based on how many names start with them, from most frequent to least frequent.

6. **Print results**: Finally, the code prints the `counts` data frame, which displays the first letter of each name along with the number of names that start with that letter.

In summary, this code takes a data frame with names, extracts the first letter of each name, counts how many names start with each letter, and presents the results in a sorted pivot table.

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