setwd("/home/daria/Courses/R/Edx/Intro/")
who <- read.csv('WHO.csv')

who_europe <- subset(who, Region == "Europe")

sd(who$Under15)

## [1] 10.53457

summary(who$Under15)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   13.12   18.72   28.65   28.73   37.75   49.99

# returns row value for country with minimum value
which.min(who$Under15)

## [1] 86

# returns country of given row 
who$Country[86]

## [1] Japan
## 194 Levels: Afghanistan Albania Algeria Andorra ... Zimbabwe

# for max
which.max(who$Under15)

## [1] 124

who$Country[124]

## [1] Niger
## 194 Levels: Afghanistan Albania Algeria Andorra ... Zimbabwe

plot(who$GNI, who$FertilityRate)

Outliers <- subset(who, GNI > 10000 & FertilityRate > 2.5)

nrow(Outliers)

## [1] 7

Outliers[c("Country","GNI","FertilityRate")]

##               Country   GNI FertilityRate
## 23           Botswana 14550          2.71
## 56  Equatorial Guinea 25620          5.04
## 63              Gabon 13740          4.18
## 83             Israel 27110          2.92
## 88         Kazakhstan 11250          2.52
## 131            Panama 14510          2.52
## 150      Saudi Arabia 24700          2.76

hist(who$CellularSubscribers)

boxplot(who$LifeExpectancy ~ who$Region)

table(who$Region)

## 
##                Africa              Americas Eastern Mediterranean 
##                    46                    35                    22 
##                Europe       South-East Asia       Western Pacific 
##                    53                    11                    27

# avr % of population over 60 in diff regions
tapply(who$Over60, who$Region, mean)

##                Africa              Americas Eastern Mediterranean 
##              5.220652             10.943714              5.620000 
##                Europe       South-East Asia       Western Pacific 
##             19.774906              8.769091             10.162963

tapply(who$LiteracyRate, who$Region, min, na.rm = TRUE)

##                Africa              Americas Eastern Mediterranean 
##                  31.1                  75.2                  63.9 
##                Europe       South-East Asia       Western Pacific 
##                  95.2                  56.8                  60.6