Surely Cherryl

New Zealand Names

This is just showing how to process the New Zealand baby names spreadsheet provided by the New Zealand Governemnt, and also make streamgraphs, available from github with devtools::install_github(“hrbrmstr/streamgraph”)

download.file("https://smartstart.services.govt.nz/assets/files/Top-baby-names-1954-2016.xlsx", destfile="babynames.xlsx", mode="wb", method="libcurl")
library(readxl)
library(dplyr)
library(streamgraph)

female <- read_excel("~/Desktop/babynames.xlsx", 
    sheet = "Girls' Names", col_names = FALSE, 
    skip = 7)
female <- female[1:100,]
male <- read_excel("~/Desktop/babynames.xlsx", 
    sheet = "Boys' Names", col_names = FALSE, 
    skip = 7)
male <- male[1:100,]

for (i in 1:62){
  female[,(i*3)+2] <- i+1953
}
female$X190 <- 2016

for (i in 1:62){
  male[,(i*3)+2] <- i+1953
}
male$X190 <- 2016

names <- 0:62*3 + 3
numbers <- 0:62*3 + 4
years <- 0:62*3 + 5

female_names <- data.frame(name= unlist(female[,names]),
                         number= unlist(female[,numbers]),
                         year= unlist(female[,years]),
                         stringsAsFactors = FALSE)

male_names <- data.frame(name= unlist(male[,names]),
                         number= unlist(male[,numbers]),
                         year= unlist(male[,years]),
                         stringsAsFactors = FALSE)

Streamgraph of female names

female_names %>% streamgraph(key=name, value=number, date=year) %>%
sg_legend(show=TRUE, label="Name: ")

Streamgraph of male names

male_names %>% streamgraph(key=name, value=number, date=year) %>%
sg_legend(show=TRUE, label="Name: ")