Read Data

# csv
read.csv("https://raw.githubusercontent.com/hadley/data-baby-names/master/baby-names.csv") %>%
  system.time()
##    user  system elapsed 
##   16.40    0.31   17.40
# fread
fread("https://raw.githubusercontent.com/hadley/data-baby-names/master/baby-names.csv") %>%
  system.time()
##    user  system elapsed 
##    0.17    0.11    0.83

Create topNames and topNames1990

babynames <- fread("https://raw.githubusercontent.com/hadley/data-baby-names/master/baby-names.csv")

topNames <- babynames %>%
mutate(decade = (year %/% 10) * 10) %>%
group_by(decade, name) %>%
summarize(Percent = mean(percent)) %>%
top_n(Percent, n = 10) %>% ungroup()
## `summarise()` has grouped output by 'decade'. You can override using the `.groups` argument.
topNames <- topNames %>% arrange(desc(Percent))

topNames1990 <- filter(topNames, decade == "1990")

colnames(topNames1990) <- c("Decade", "Name", "Percent", "Position")

Create topNames1990 table

Top 10 names for babies in the 1990’s in the U.S.
Name Percent
Matthew 0.01708
Joshua 0.01597
Christopher 0.01593
Michael 0.01498
Jacob 0.01457
Nicholas 0.01341
Andrew 0.01325
Daniel 0.01321
Jessica 0.01279
Joseph 0.01266

Top Names of the Nineties Plot 

topNames1980 <- filter(topNames, decade == "1980")

## Most Common name in 1980's was Michael ##