Introduction

You will use this code as a template for your Visualization 3 assignment. The first step is to call a set of packages that you might use in this assignment. The final choices belong to you.

Note that each code chunk is set off with special tags.

library(tidyverse)
library(ggvis)
library(WDI)
library(plotly)

Call package `WDI` to retrieve most updated figures available.

In this assignment, we need to update 8 data series from the WDI:

Tableau Name	WDI Series
Birth Rate	SP.DYN.CBRT.IN
Health Exp % GDP	SH.XPD.TOTL.ZS
Health Exp/Capita	SH.XPD.PCAP
Infant Mortality Rate	SP.DYN.IMRT.IN
Internet Usage	IT.NET.USER.ZS
Life Expectancy (Total)	SP.DYN.LE00.IN
Mobile Phone Usage	IT.CEL.SETS.P2
Population Total	SP.POP.TOTL

The next code chunk will call the WDI API and fetch the years 2000 through 2017, as available. It will then remove the country regional and other aggregates.

birth <- "SP.DYN.CBRT.IN"
hxpgdp <- "SH.XPD.TOTL.ZS"
hxpcap <- "SH.XPD.PCAP"
infmort <- "SP.DYN.IMRT.IN"
net <-"IT.NET.USER.ZS"
lifeexp <- "SP.DYN.LE00.IN"
mobile <- "IT.CEL.SETS.P2"
pop <- "SP.POP.TOTL"

# create a vector of the desired indicator series
indicators <- c(birth, hxpgdp, hxpcap, infmort, net, lifeexp, mobile, pop)

newdata <- WDI(country="all", indicator = indicators, 
     start = 2000, end = 2017, extra = TRUE)

# remove country groupings
newdata$longitude[newdata$longitude==""] <- NA
countries <- filter(newdata, !is.na(longitude))  # drop aggregate groups
## rename columns for each of reference
countries <- rename(countries, birth = SP.DYN.CBRT.IN, 
       hxpgdp = SH.XPD.TOTL.ZS, hxpcap = SH.XPD.PCAP, 
       infmort = SP.DYN.IMRT.IN, net  = IT.NET.USER.ZS,
       lifeexp = SP.DYN.LE00.IN, mobile = IT.CEL.SETS.P2, 
       pop = SP.POP.TOTL)

glimpse(countries) ## data frame column names appear here

## Observations: 3,775
## Variables: 18
## $ iso2c     <chr> "AD", "AD", "AD", "AD", "AD", "AD", "AD", "AD", "AD"...
## $ country   <chr> "Andorra", "Andorra", "Andorra", "Andorra", "Andorra...
## $ year      <dbl> 2016, 2005, 2000, 2004, 2015, 2014, 2006, 2017, 2002...
## $ birth     <dbl> 8.800, 10.700, 11.300, 10.900, NA, NA, 10.600, NA, 1...
## $ hxpgdp    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ hxpcap    <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ infmort   <dbl> 3.3, 4.1, 4.7, 4.2, 3.4, 3.5, 4.1, 3.2, 4.5, 3.9, 4....
## $ net       <dbl> 97.93064, 37.60577, 10.53884, 26.83795, 96.91000, 95...
## $ lifeexp   <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...
## $ mobile    <dbl> 98.51322, 81.85933, 36.00398, 76.55160, 91.44000, 83...
## $ pop       <dbl> 77281, 78867, 65390, 76244, 78014, 79223, 80991, 769...
## $ iso3c     <fct> AND, AND, AND, AND, AND, AND, AND, AND, AND, AND, AN...
## $ region    <fct> Europe & Central Asia, Europe & Central Asia, Europe...
## $ capital   <fct> Andorra la Vella, Andorra la Vella, Andorra la Vella...
## $ longitude <fct> 1.5218, 1.5218, 1.5218, 1.5218, 1.5218, 1.5218, 1.52...
## $ latitude  <fct> 42.5075, 42.5075, 42.5075, 42.5075, 42.5075, 42.5075...
## $ income    <fct> High income, High income, High income, High income, ...
## $ lending   <fct> Not classified, Not classified, Not classified, Not ...

Population Health Indicators graph (Tableau tab 2)

Replace this text chunk with an explanation of your approach to the second graph, which averages the measures over all available years. How did you achieve the colored rectangles, or did you need to take an alternative approach?*

## Your plotting code goes here

Replace this text chunk with a sentence comparing this graph to the original Tableau version. Has the world changed much?

Care Spending 2015 (Tableau tab 3)

Replace this text chunk with an explanation of your approach to this graph, commenting on how you included a slider to allow users to choose a year.*

## Your plotting code goes here

Replace this text chunk with a sentence comparing this graph to the original Tableau version. Are the same countries still at the top of the list?

Technology graph (Tableau tab 4)

Replace this text chunk with an explanation of your approach to this graph.*

## Your plotting code goes here

Replace this text chunk with a sentence comparing this graph to the original Tableau version. Has the world changed much?

Conclusion

** write a sentence or two summarizing noteworthy changes in recent years. #####