Load libraries

library(ggplot2)
library(ggthemes)
# Set the theme to theme_solarized where the font size is 20
theme_set(theme_solarized(20)) 

Load data into a dataframe

deaths <- read.csv('childdeathnumbers.csv', header = TRUE)

Create histograms

# Create a histogram of "Number of deaths" v/s "Counts of Countries"
ggplot(aes(x = X2008), data = deaths) +
  geom_histogram(color = 'black', fill = 'red', binwidth = 35000) + 
  scale_x_continuous(limit = c(0, 950000), breaks = seq(0, 950000, 35000)) +
  xlab('Number of Deaths in 2008') +
  ylab('Counts of Countries with that many Deaths')

ggsave('deathshistogram.jpg')

## Saving 7 x 5 in image

# Get a summary
summary(deaths$X2008)

##     Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
##      4.0    238.8   1928.0  29320.0  15540.0 826100.0

# Create a subset for countries which have more than 10000 deaths
deathssub = subset(deaths, deaths$X2008 >= 10000)

# Create a histogram of "Number of deaths" v/s "Counts of Countries"
ggplot(aes(x = X2008), data = deathssub) +
  geom_histogram(color = 'black', fill = 'red', binwidth = 35000) + 
  scale_x_continuous(limit = c(0, 950000), breaks = seq(0, 950000, 35000)) +
  xlab('Number of Deaths in 2008') +
  ylab('Counts of Countries with that many Deaths')

ggsave('deathshistogramsubset.jpg')

## Saving 7 x 5 in image

Create frequency plots

ggplot(aes(x = X2008), data = deaths) +
  geom_freqpoly(color = 'purple', binwidth = 35000) +
  xlab('Number of Deaths in 2008') +
  ylab('Counts of Countries with that many Deaths')

ggsave('deathsfrequency.jpg')

## Saving 7 x 5 in image

ggplot(aes(x = X2008), data = deathssub) +
  geom_freqpoly(color = 'purple', binwidth = 18000) +   
  scale_x_continuous(limit = c(0, 950000), breaks = seq(0, 950000, 36000)) +
  xlab('Number of Deaths in 2008') +
  ylab('Counts of Countries with that many Deaths')

## Warning: Removed 2 rows containing missing values (geom_path).

ggsave('deathsfrequencysubset.jpg')

## Saving 7 x 5 in image

## Warning: Removed 2 rows containing missing values (geom_path).