Improved explorations

4-explore.r

@@ -1,15 +1,45 @@
+library(ggplot2)
+all <- read.csv("baby-names.csv", stringsAsFactors = FALSE)
+all$sex <- factor(all$sex, levels = c("girl", "boy"))
+sump <- colwise(sum, "percent")
 
+# Investigate the percentage of all names that the top 1000 baby names
+# occupies
+ofall <- ddply(all, .(year, sex), sump)
+qplot(year, percent, data = ofall, colour = sex, geom = "line") + ylim(0, 1)
+# Recently trending down - names are become more diverse?
 
-ofall <- ddply(all, .(year, sex), function(df) sum(df$percent))
-library(ggplot2)
-qplot(year, V1, data = ofall, colour = sex, geom = "line") + ylim(0, 1)
 
+# Trends in various letters --------------------------------------------
+
+# Helper function to extract letter at given position.  Negative values
+# index from rear of string.
+letter <- function(string, pos) {
+  if (pos > 0) {
+    substr(string, pos, pos) 
+  } else {
+    nc <- nchar(string)
+    substr(string, nc + pos + 1, nc + pos + 1)
+  }
+}
 
-all$lastletter <- with(all, substr(name, nchar(name), nchar(name)))
+axes <- list(
+  scale_x_continuous(breaks = c(1900, 1950, 2000)),
+  scale_y_continuous("", limits = c(0, 0.4), formatter = "percent")
+)
 
-ll <- ddply(all, .(year, sex, lastletter), function(df) sum(df$percent))
-qplot(year, V1, data = ll, colour = sex, geom = "line") + 
-  facet_wrap(~ lastletter) + 
-  scale_x_continuous(breaks = c(1900, 1950, 2000))
-
+# Last letter
+ll <- ddply(all, .(year, sex, last = letter(name, -1)), sump)
+qplot(year, percent, data = ll, colour = sex, geom = "line") + 
+  facet_wrap(~ last) + axes
 last_plot() + scale_y_log10()
+
+# First letter
+fl <- ddply(all, .(year, sex, first = letter(name, 1)), sump)
+qplot(year, percent, data = fl, colour = sex, geom = "line") + 
+  facet_wrap(~ first) + axes
+
+# Second letter?
+sl <- ddply(all, .(year, sex, second = letter(name, 2)), sump)
+qplot(year, percent, data = sl, colour = sex, geom = "line") + 
+  facet_wrap(~ second) + axes