hmdR- Use the "Human Mortality Population Database" and more ggplot2 enhancements

Copyright 2016 Ramanathan Perumal. Licensed under the MIT license. ❄️⛄

Installation 💻📥📚

hmdR is available through GitHub.

To install the latest version from GitHub:

install.packages("devtools")
devtools::install_github("ramamet/hmdR")

Usage 🏢🔧📇

We'll first load the package, and then see how all the functions work.

library("hmdR")

As a simple first example, let's load a hmd_pop dataset with 453927 rows and 10 columns where the Year values are recorded time periods and the Age values are classified from 0-100 years , and plot a simple ggplot2 scatterplot.

 data(hmd_pop)

Understanding the database with basic descriptive statistics;

head(hmd_pop)

  Year Age   Female     Male    Total  agebins sex.ratio sex.ratio.bins country  code
1 1921   1 57777.30 60216.58 117993.9 Age;0-25  1.042219       1.0-1.25     AUS  AUS
2 1921   2 56940.78 59047.16 115987.9 Age;0-25  1.036992       1.0-1.25     AUS  AUS
3 1921   3 58272.29 60217.82 118490.1 Age;0-25  1.033387       1.0-1.25     AUS  AUS
4 1921   4 58718.95 60773.16 119492.1 Age;0-25  1.034984       1.0-1.25     AUS  AUS
5 1921   5 59887.79 61686.66 121574.4 Age;0-25  1.030037       1.0-1.25     AUS  AUS
6 1921   6 61033.62 62332.64 123366.3 Age;0-25  1.021284       1.0-1.25     AUS  AUS

Number of datapoints available by country;

 table(hmd_pop$country)
 
     AUS     AUT     BEL     BGR     BLR     CAN     CHE     CHL     CZE   DEUTE 
    9290    6965   16919    6565    5757    9191   13953    1515    6666    5959 
  DEUTNP   DEUTW     DNK     ESP     EST     FIN  FRACNP  FRATNP GBRCENW GBR_NIR 
    2525    5959   18058   10807    5639   13506   19392   19392   17574    9388 
  GBR_NP GBR_SCO GBRTENW     GRC     HUN     IRL     ISL     ISR     ITA     JPN 
    9393   16132   17574    3434    6661    6666   17468    3333   13888    6868 
     LTU     LUX     LVA     NLD     NOR  NZL_MA  NZL_NM  NZL_NP     POL     PRT 
    5656    5581    5656   16429   17124    5923   10752    6666    5757    7474 
     RUS     SVK     SVN     SWE     TWN     UKR     USA 
    5454    6651    3320   26564    4545    5656    8282 

Basic ggplot type; 🌌

Checking the tool with initial test,

 gghmd(hmd_pop)  

There are several more parameters can be add in the plot, here is an example with a few more being used. Note that you can use any function that the gghmd_loc or gghmd_yr layers accept, and additional ggplot layers will be passed to base layers, such as facet_wrap(~country) and Year in the following example.

gghmd_map() function; 🌍🌎🌏

gghmd_map(hmd_pop,yrMin,yrMax,yrDiv,aAge) format

 gghmd_map(hmd_pop,1980,2010,10,30) 

gghmd_yr() function; 📅

gghmd_yr(hmd_pop,yrMin,yrMax) format

gghmd_yr(hmd_pop,1940,2000)

gghmd_time() function; 💹📈

gghmd_time(hmd_pop,yrMin,yrMax) format

  gghmd_time(hmd_pop,1970,2000)

gghmd_bar() function; 📊

gghmd_bar(hmd_pop,country,ageMin,ageMax,yrMin,yrMax) format

gghmd_bar(hmd_pop,"USA",80,90,1970,2000)

gghmd_loc() function; 🌈🔍

gghmd_loc(hmd_pop,country,yrMin,yrMax) format

gghmd_loc(hmd_pop,'USA',1930,2000)

rawData 🏥📒📋

National Center for Health Statistics. Vital Statistics of the United States, Volume II: Mortality, Part A. Washington, D.C.: Government Printing Office, various years. (Data obtained through the Human Mortality Database, www.mortality.org or www.humanmortality.de, on [date].)

contact 📫📦

If you would like to contribute further on this package or bugs, please respond me by [email protected].