Babynames: Vowels Over Time

Hypothesis

My hypothesis is that the proportion of baby names starting with vowels has been increasing over the years.

First, I’ll install the necessary packages.

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
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✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.0     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
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ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(babynames)
library(scales)

Attaching package: 'scales'

The following object is masked from 'package:purrr':

    discard

The following object is masked from 'package:readr':

    col_factor

The external dataset was loaded here:

canada_babynames <- read_csv("StateNames.csv")

Rows: 5647426 Columns: 6
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (3): Name, Gender, State
dbl (3): Id, Year, Count

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

I found the state names data on Kaggle.

Observation 1:

Hypothesis: The proportion of baby names starting with ‘A’ has increased over time.# Filter names starting with ‘A’

a_names <- babynames %>%
  filter(substr(name, 1, 1) == "A")

a_name_proportions <- a_names %>%
  group_by(year) %>%
  summarize(proportion = sum(n))

ggplot(a_name_proportions, aes(x = year, y = proportion)) +
  geom_line() +
  labs(title = "Total Number of Baby Names Starting with 'A' Over Time",
       x = "Year",
       y = "Number of Names") +
  scale_y_continuous(labels = comma) + # Format y-axis labels with commas
  theme_minimal()