DeathRate Data

library(RCurl)

## Loading required package: bitops

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(tidyr)

## 
## Attaching package: 'tidyr'

## The following object is masked from 'package:RCurl':
## 
##     complete

library(useful)

## Loading required package: ggplot2

URL <- getURL("https://raw.githubusercontent.com/DanielBrooks39/IS607/master/Project%202/Death%20Rate%20Data.csv")
DeathData <- read.csv(text = URL, header = TRUE)

tbl_df(DeathData)

## Source: local data frame [88 x 5]
## 
##     Year         Ages Both.sexes   Female     Male
##    (int)       (fctr)      (dbl)    (dbl)    (dbl)
## 1   2013      <1 year   0.034922 0.032553 0.037135
## 2   2013    1-4 years   0.003233 0.003312 0.003158
## 3   2013    5-9 years   0.001410 0.001397 0.001422
## 4   2013  10-14 years   0.000916 0.000894 0.000937
## 5   2013 15-19  years   0.001230 0.001102 0.001351
## 6   2013  20-24 years   0.001563 0.001305 0.001807
## 7   2013  25-29 years   0.001780 0.001490 0.002057
## 8   2013  30-34 years   0.002150 0.001771 0.002517
## 9   2013  35-39 years   0.002631 0.002117 0.003132
## 10  2013  40-44 years   0.003163 0.002478 0.003834
## ..   ...          ...        ...      ...      ...

names(DeathData) <- c("Year", "Ages", "Both_Sexes", "Females", "Males")
TidyData <- gather(DeathData, "Sex","DeathRate", 3:5)

Bar Plot of Death Rates by Sex

TidyData$Ages <- factor(TidyData$Ages, levels = c("<1 year", "1-4 years", "5-9 years", "10-14 years", "15-19 years", "20-24 years", "25-29 years", "30-34 years", "35-39 years", "40-44 years", "45-49 years", "50-54 years", "55-59 years", "60-64 years", "65-69 years", "70-74 years", "75-79 years", "80-84 years", "85-89 years", "90-94 years", "95-99 years", "100+ years"))

ggplot(TidyData, aes(x=Sex, y=DeathRate, fill = Ages)) + geom_bar(stat = "identity", position="dodge") + theme(axis.title.x=element_text(face="bold", size=15), axis.title.y=element_text(face="bold", size=15), axis.text=element_text(face="bold", size = 10)) + ggtitle("Death Rate") + theme(plot.title=element_text(face="bold", size=20)) + theme(legend.title=element_text(face="bold", size=10,color="white"), legend.background=element_rect(fill="black"), legend.text=element_text(face="bold", color="white", size=8))

* This is a bar plot that is separated by sex(Males, Females, Both). We can see by the graph that teh death rate increases the older you get (As it should be). It is a little scary that infants below the age of 1 do have a little high of a death rate. The graph is a really good depiction of how the rate changes as you get older.