Name analysis

1. This will determine the rank of the name Nicole among females in 2000 by popularity.

babynames %>%                             
  filter(year == 2000, sex == "F") %>%    
  mutate(rank = row_number()) %>%         
  mutate(percent = round(prop * 100, 1)) %>% 
  filter(name == "Nicole")               

Nicole was the 31st most popular name in the year 2000.

2. This will create a word cloud of popular names of females in 2000.

babynames %>%
  filter(year == 2000) %>%     
  filter(sex == "F") %>%       
  select(name, n) %>%           
  top_n(100, n) %>%           
  wordcloud2(size = , color = "pink")                 

3. This will create a graph of the popularity of the name Nicole throughout time.

babynames %>%                                    
  filter(name == "Nicole", sex == "F") %>%      
  ggplot(aes(x = year, y = prop)) +              
  geom_line()                                    

It looks like the name Nicole reached its peak in popularity in the mid-1980’s. In 2000, the year I was born, the popularity Nicole steadily decreased until the 2010’s.

4. This will create a table of the top 10 years the name Nicole was most popular.

babynames %>%                                  
  filter(name == "Nicole", sex == "F") %>%    
  top_n(10, prop) %>%                          
  arrange(-prop)                               

NA

5. This will create a graph comparing the popularity of the names Nicole, Allison, and Tristin over time.

babynames %>%
  filter(name == "Nicole" | name == "Allison" | name == "Tristin") %>% 
  filter(sex == "F") %>% 
  ggplot(aes(x = year, y = n, color = name)) +
  geom_line()

This shows that out of the three names, Nicole was the most popular but is slowly losing popularity, the name Allison has gained popularity, and the name Tristin is consistently less used.