8 * 6
## [1] 48
2^16
## [1] 65536
abs(-65)
SquareRoot9 = sqrt(9)
SquareRoot9
## [1] 3
HoursYear <- 365 * 24
HoursYear
## [1] 8760
ls()
## [1] "HoursYear" "SquareRoot9"
c(2, 3, 5, 8, 13)
## [1] 2 3 5 8 13
Country = c("Brazil", "China", "India", "Switzerland", "USA")
LifeExpectancy = c(74, 76, 65, 83, 79)
Country
## [1] "Brazil" "China" "India" "Switzerland" "USA"
LifeExpectancy
## [1] 74 76 65 83 79
c("Brazil", 74, "China", 76)
## [1] "Brazil" "74" "China" "76"
Country[1]
## [1] "Brazil"
LifeExpectancy[3]
## [1] 65
Sequence = seq(1, 100, 2)
Sequence
## [1] 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45
## [24] 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87 89 91
## [47] 93 95 97 99
Data = data.frame(Country, LifeExpectancy)
Data
## Country LifeExpectancy
## 1 Brazil 74
## 2 China 76
## 3 India 65
## 4 Switzerland 83
## 5 USA 79
Population = c(199000, 1390000, 1240000, 7997, 318000)
Data2 = cbind(Data, Population)
Data2
## Country LifeExpectancy Population
## 1 Brazil 74 199000
## 2 China 76 1390000
## 3 India 65 1240000
## 4 Switzerland 83 7997
## 5 USA 79 318000
Country = c("Australia", "Greece")
LifeExpectancy = c(82, 81)
Population = c(23050, 11125)
NewData = data.frame(Country, LifeExpectancy, Population)
NewData
## Country LifeExpectancy Population
## 1 Australia 82 23050
## 2 Greece 81 11125
Data3 = rbind(Data2, NewData)
Data3
## Country LifeExpectancy Population
## 1 Brazil 74 199000
## 2 China 76 1390000
## 3 India 65 1240000
## 4 Switzerland 83 7997
## 5 USA 79 318000
## 6 Australia 82 23050
## 7 Greece 81 11125
setwd("~/Desktop/Manalytics/W1 intro R")
WHO = read.csv("WHO.csv")
str(WHO)
## 'data.frame': 194 obs. of 13 variables:
## $ Country : Factor w/ 194 levels "Afghanistan",..: 1 2 3 4 5 6 7 8 9 10 ...
## $ Region : Factor w/ 6 levels "Africa","Americas",..: 3 4 1 4 1 2 2 4 6 4 ...
## $ Population : int 29825 3162 38482 78 20821 89 41087 2969 23050 8464 ...
## $ Under15 : num 47.4 21.3 27.4 15.2 47.6 ...
## $ Over60 : num 3.82 14.93 7.17 22.86 3.84 ...
## $ FertilityRate : num 5.4 1.75 2.83 NA 6.1 2.12 2.2 1.74 1.89 1.44 ...
## $ LifeExpectancy : int 60 74 73 82 51 75 76 71 82 81 ...
## $ ChildMortality : num 98.5 16.7 20 3.2 163.5 ...
## $ CellularSubscribers : num 54.3 96.4 99 75.5 48.4 ...
## $ LiteracyRate : num NA NA NA NA 70.1 99 97.8 99.6 NA NA ...
## $ GNI : num 1140 8820 8310 NA 5230 ...
## $ PrimarySchoolEnrollmentMale : num NA NA 98.2 78.4 93.1 91.1 NA NA 96.9 NA ...
## $ PrimarySchoolEnrollmentFemale: num NA NA 96.4 79.4 78.2 84.5 NA NA 97.5 NA ...
summary(WHO)
## Country Region Population
## Afghanistan : 1 Africa :46 Min. : 1
## Albania : 1 Americas :35 1st Qu.: 1696
## Algeria : 1 Eastern Mediterranean:22 Median : 7790
## Andorra : 1 Europe :53 Mean : 36360
## Angola : 1 South-East Asia :11 3rd Qu.: 24535
## Antigua and Barbuda: 1 Western Pacific :27 Max. :1390000
## (Other) :188
## Under15 Over60 FertilityRate LifeExpectancy
## Min. :13.1 Min. : 0.81 Min. :1.26 Min. :47.0
## 1st Qu.:18.7 1st Qu.: 5.20 1st Qu.:1.83 1st Qu.:64.0
## Median :28.6 Median : 8.53 Median :2.40 Median :72.5
## Mean :28.7 Mean :11.16 Mean :2.94 Mean :70.0
## 3rd Qu.:37.8 3rd Qu.:16.69 3rd Qu.:3.90 3rd Qu.:76.0
## Max. :50.0 Max. :31.92 Max. :7.58 Max. :83.0
## NA's :11
## ChildMortality CellularSubscribers LiteracyRate GNI
## Min. : 2.20 Min. : 2.57 Min. :31.1 Min. : 340
## 1st Qu.: 8.43 1st Qu.: 63.57 1st Qu.:71.6 1st Qu.: 2335
## Median : 18.60 Median : 97.75 Median :91.8 Median : 7870
## Mean : 36.15 Mean : 93.64 Mean :83.7 Mean :13321
## 3rd Qu.: 55.98 3rd Qu.:120.81 3rd Qu.:97.8 3rd Qu.:17558
## Max. :181.60 Max. :196.41 Max. :99.8 Max. :86440
## NA's :10 NA's :91 NA's :32
## PrimarySchoolEnrollmentMale PrimarySchoolEnrollmentFemale
## Min. : 37.2 Min. : 32.5
## 1st Qu.: 87.7 1st Qu.: 87.3
## Median : 94.7 Median : 95.1
## Mean : 90.8 Mean : 89.6
## 3rd Qu.: 98.1 3rd Qu.: 97.9
## Max. :100.0 Max. :100.0
## NA's :93 NA's :93
head(WHO)
## Country Region Population Under15 Over60
## 1 Afghanistan Eastern Mediterranean 29825 47.42 3.82
## 2 Albania Europe 3162 21.33 14.93
## 3 Algeria Africa 38482 27.42 7.17
## 4 Andorra Europe 78 15.20 22.86
## 5 Angola Africa 20821 47.58 3.84
## 6 Antigua and Barbuda Americas 89 25.96 12.35
## FertilityRate LifeExpectancy ChildMortality CellularSubscribers
## 1 5.40 60 98.5 54.26
## 2 1.75 74 16.7 96.39
## 3 2.83 73 20.0 98.99
## 4 NA 82 3.2 75.49
## 5 6.10 51 163.5 48.38
## 6 2.12 75 9.9 196.41
## LiteracyRate GNI PrimarySchoolEnrollmentMale
## 1 NA 1140 NA
## 2 NA 8820 NA
## 3 NA 8310 98.2
## 4 NA NA 78.4
## 5 70.1 5230 93.1
## 6 99.0 17900 91.1
## PrimarySchoolEnrollmentFemale
## 1 NA
## 2 NA
## 3 96.4
## 4 79.4
## 5 78.2
## 6 84.5
head(WHO, 2)
## Country Region Population Under15 Over60
## 1 Afghanistan Eastern Mediterranean 29825 47.42 3.82
## 2 Albania Europe 3162 21.33 14.93
## FertilityRate LifeExpectancy ChildMortality CellularSubscribers
## 1 5.40 60 98.5 54.26
## 2 1.75 74 16.7 96.39
## LiteracyRate GNI PrimarySchoolEnrollmentMale
## 1 NA 1140 NA
## 2 NA 8820 NA
## PrimarySchoolEnrollmentFemale
## 1 NA
## 2 NA
WHO_Europe = subset(WHO, Region == "Europe")
str(WHO_Europe)
## 'data.frame': 53 obs. of 13 variables:
## $ Country : Factor w/ 194 levels "Afghanistan",..: 2 4 8 10 11 16 17 22 26 43 ...
## $ Region : Factor w/ 6 levels "Africa","Americas",..: 4 4 4 4 4 4 4 4 4 4 ...
## $ Population : int 3162 78 2969 8464 9309 9405 11060 3834 7278 4307 ...
## $ Under15 : num 21.3 15.2 20.3 14.5 22.2 ...
## $ Over60 : num 14.93 22.86 14.06 23.52 8.24 ...
## $ FertilityRate : num 1.75 NA 1.74 1.44 1.96 1.47 1.85 1.26 1.51 1.48 ...
## $ LifeExpectancy : int 74 82 71 81 71 71 80 76 74 77 ...
## $ ChildMortality : num 16.7 3.2 16.4 4 35.2 5.2 4.2 6.7 12.1 4.7 ...
## $ CellularSubscribers : num 96.4 75.5 103.6 154.8 108.8 ...
## $ LiteracyRate : num NA NA 99.6 NA NA NA NA 97.9 NA 98.8 ...
## $ GNI : num 8820 NA 6100 42050 8960 ...
## $ PrimarySchoolEnrollmentMale : num NA 78.4 NA NA 85.3 NA 98.9 86.5 99.3 94.8 ...
## $ PrimarySchoolEnrollmentFemale: num NA 79.4 NA NA 84.1 NA 99.2 88.4 99.7 97 ...
write.csv(WHO_Europe, "WHO_Europe.csv")
rm(WHO_Europe)
mean(WHO$Under15)
## [1] 28.73
sd(WHO$Under15)
## [1] 10.53
summary(WHO$Under15)
## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 13.1 18.7 28.6 28.7 37.8 50.0
which.min(WHO$Under15)
## [1] 86
WHO$Country[86]
## [1] Japan
## 194 Levels: Afghanistan Albania Algeria Andorra ... Zimbabwe
which.max(WHO$Under15)
## [1] 124
WHO$Country[124]
## [1] Niger
## 194 Levels: Afghanistan Albania Algeria Andorra ... Zimbabwe
WHO$Country[which.max(WHO$Under15)]
## [1] Niger
## 194 Levels: Afghanistan Albania Algeria Andorra ... Zimbabwe
sort(WHO$Under15)
## [1] 13.12 13.17 13.28 13.53 14.04 14.04 14.16 14.18 14.41 14.51 14.56
## [12] 14.57 14.60 14.62 14.79 14.91 14.92 14.98 14.98 15.00 15.05 15.10
## [23] 15.13 15.20 15.20 15.25 15.45 15.69 16.35 16.37 16.42 16.45 16.48
## [34] 16.52 16.58 16.71 16.88 16.89 17.16 17.21 17.46 17.54 17.62 17.66
## [45] 17.95 18.26 18.26 18.47 18.64 18.95 18.99 19.01 19.63 20.16 20.17
## [56] 20.26 20.34 20.71 20.73 21.33 21.38 21.54 21.62 21.64 21.95 21.98
## [67] 22.05 22.25 22.87 23.22 23.68 23.94 24.19 24.31 24.42 24.56 24.90
## [78] 25.15 25.28 25.46 25.70 25.75 25.96 25.96 25.96 26.00 26.65 26.96
## [89] 27.05 27.42 27.53 27.78 27.83 27.85 28.03 28.53 28.65 28.65 28.84
## [100] 28.88 28.90 29.02 29.03 29.18 29.27 29.43 29.45 29.53 29.69 30.10
## [111] 30.10 30.10 30.10 30.17 30.21 30.29 30.53 30.57 30.61 30.61 30.61
## [122] 30.62 31.23 31.25 32.78 33.37 33.72 33.75 34.13 34.31 34.40 34.53
## [133] 35.23 35.35 35.35 35.58 35.61 35.72 35.75 35.81 36.59 36.75 36.77
## [144] 37.33 37.37 37.88 38.05 38.37 38.49 38.59 38.95 40.07 40.22 40.24
## [155] 40.37 40.51 40.72 40.80 41.48 41.48 41.55 41.60 41.74 41.89 42.17
## [166] 42.28 42.37 42.37 42.46 42.72 42.95 43.06 43.08 43.10 43.29 43.54
## [177] 43.56 44.20 44.23 44.85 45.11 45.38 45.44 45.66 45.90 46.33 46.73
## [188] 47.14 47.35 47.42 47.58 48.52 48.54 49.99
head(sort(WHO$Under15), 4)
## [1] 13.12 13.17 13.28 13.53
plot(WHO$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)
hist(WHO$CellularSubscribers)
boxplot(WHO$LifeExpectancy ~ WHO$Region)
boxplot(WHO$LifeExpectancy ~ WHO$Region, xlab = "Region", ylab = "Life Expectancy",
main = "Life Expectancy of Countries by Region")
table(WHO$Region)
##
## Africa Americas Eastern Mediterranean
## 46 35 22
## Europe South-East Asia Western Pacific
## 53 11 27
tapply(WHO$Over60, WHO$Region, mean)
## Africa Americas Eastern Mediterranean
## 5.221 10.944 5.620
## Europe South-East Asia Western Pacific
## 19.775 8.769 10.163
tapply(WHO$LiteracyRate, WHO$Region, min)
## Africa Americas Eastern Mediterranean
## NA NA NA
## Europe South-East Asia Western Pacific
## NA NA NA
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