In February 2017, the United Arab Emirates held a full-day World Happiness meeting, as part of the World Government Summit. Now on World Happiness Day, March 20th, we launch the World Happiness Report 2017, once again back at the United Nations, again published by the Sustainable Development Solutions Network, and now supported by a generous three-year grant from the Ernesto Illy Foundation.

Load the file

head(happy_2017)

Descriptive Statistics

Quantiles plot

ggplot(data = happy_2017,aes(x="Region",y=Freedom))+geom_boxplot(aes(fill=Region))

Variance and Standard Deviation

var(happy_2017$Happiness.Score)

## [1] 1.246317

sqrt(var(happy_2017$Happiness.Score))

## [1] 1.116386

sd(happy_2017$Happiness.Score)

## [1] 1.116386

Summary Statistics

library(knitr)
kable(summary(happy_2017))

Country	Region	Happiness.Rank	Happiness.Score	Economy..GDP.per.Capita.	Family	Health..Life.Expectancy.	Freedom	Generosity	Trust..Government.Corruption.	Dystopia.Residual
Afghanistan: 1	Sub-Saharan Africa :36	Min. : 1.00	Min. :2.905	Min. :0.02264	Min. :0.3961	Min. :0.005565	Min. :0.0000	Min. :0.0000	Min. :0.00000	Min. :0.3779
Albania : 1	Central and Eastern Europe :29	1st Qu.: 39.25	1st Qu.:4.519	1st Qu.:0.71891	1st Qu.:1.0494	1st Qu.:0.398654	1st Qu.:0.3022	1st Qu.:0.1523	1st Qu.:0.05717	1st Qu.:1.6016
Algeria : 1	Latin America and Caribbean :22	Median : 77.50	Median :5.286	Median :1.06695	Median :1.2548	Median :0.609627	Median :0.4389	Median :0.2312	Median :0.08957	Median :1.8298
Angola : 1	Western Europe :21	Mean : 77.19	Mean :5.380	Mean :0.99260	Mean :1.1971	Mean :0.557302	Mean :0.4091	Mean :0.2458	Mean :0.12247	Mean :1.8550
Argentina : 1	Middle East and Northern Africa:19	3rd Qu.:115.75	3rd Qu.:6.103	3rd Qu.:1.31503	3rd Qu.:1.4190	3rd Qu.:0.717596	3rd Qu.:0.5199	3rd Qu.:0.3240	3rd Qu.:0.15264	3rd Qu.:2.1477
Armenia : 1	Southeastern Asia : 8	Max. :154.00	Max. :7.537	Max. :1.87077	Max. :1.6106	Max. :0.949492	Max. :0.6582	Max. :0.8381	Max. :0.46431	Max. :3.1175
(Other) :144	(Other) :15	NA	NA	NA	NA	NA	NA	NA	NA	NA

Histogram

g<-ggplot(data=happy_2017,aes(Freedom))
g+geom_histogram(bins = 15)

Density Plot

g+geom_density()

Correlation

##correlation
kable(cor(happy_2017[4:11]))

	Happiness.Score	Economy..GDP.per.Capita.	Family	Health..Life.Expectancy.	Freedom	Generosity	Trust..Government.Corruption.	Dystopia.Residual
Happiness.Score	1.0000000	0.8080129	0.7476163	0.7783037	0.5784059	0.1603838	0.4422911	0.5066391
Economy..GDP.per.Capita.	0.8080129	1.0000000	0.6751627	0.8316497	0.3757427	-0.0232999	0.3561506	0.0593484
Family	0.7476163	0.6751627	1.0000000	0.6023747	0.4337487	0.0652770	0.2360538	0.1001615
Health..Life.Expectancy.	0.7783037	0.8316497	0.6023747	1.0000000	0.3597246	0.0568294	0.2826280	0.0928880
Freedom	0.5784059	0.3757427	0.4337487	0.3597246	1.0000000	0.3154470	0.4950476	0.0942454
Generosity	0.1603838	-0.0232999	0.0652770	0.0568294	0.3154470	1.0000000	0.2882775	-0.1128735
Trust..Government.Corruption.	0.4422911	0.3561506	0.2360538	0.2826280	0.4950476	0.2882775	1.0000000	0.0058970
Dystopia.Residual	0.5066391	0.0593484	0.1001615	0.0928880	0.0942454	-0.1128735	0.0058970	1.0000000

Correlation Plot

#install.packages("corrplot")

library(corrplot)
corrplot(cor(happy_2017[4:11]))

plot(happy_2017[4:11])

Analysis and Visualization

attach(happy_2017)
table(Region)

## Region
##       Australia and New Zealand      Central and Eastern Europe 
##                               2                              29 
##                    Eastern Asia     Latin America and Caribbean 
##                               4                              22 
## Middle East and Northern Africa                   North America 
##                              19                               2 
##               Southeastern Asia                   Southern Asia 
##                               8                               7 
##              Sub-Saharan Africa                  Western Europe 
##                              36                              21

Regions <- table(Region) %>% as.data.frame()

ggplot(data=Regions,aes(Region,Freq))+geom_col(aes(fill= Region))+ggtitle("No of Country from Different Region")+coord_flip()

head(arrange(happy_2017,desc(Happiness.Rank)),10)

Top 10 Happiest countries

top_10<- head(arrange(happy_2017,Happiness.Rank),10)
top_10$Country<- as.factor(top_10$Country)

top_10

ggplot(top_10, aes(x = reorder(Country,-Happiness.Score), y = Happiness.Score, fill = Country)) +
  geom_bar(stat = "identity") +
  labs(title = "Top 10 World's Happiest Countries")+ theme(axis.text.x = element_text(angle = 90))

Unhappy_country <- head(arrange(happy_2017,desc(Happiness.Rank)),10)
Unhappy_country

ggplot(Unhappy_country,aes(x=reorder(Country,Happiness.Score), y=Economy..GDP.per.Capita.,fill=Country))+geom_bar(stat = "Identity")+labs(title="GDP Per capita of Unhappy country",x="Country Name",y="Gdp Per Capita")+coord_flip()

poor_country<-head(arrange(happy_2017,Economy..GDP.per.Capita.),10)

ggplot(poor_country,aes(x=reorder(Country,Economy..GDP.per.Capita.),y=Freedom))+geom_bar(stat = "identity",aes(fill=Country))+labs(title="Freedom in Poor country")+theme_minimal()+theme(legend.position="",axis.text.x=element_text(angle=90, hjust=1))

#Most corrupt country 
corrupt_country<-head(arrange(happy_2017,Trust..Government.Corruption.),10)
ggplot(corrupt_country,aes(x=reorder(Country,Trust..Government.Corruption.),y=Trust..Government.Corruption.,fill=Country))+geom_bar(stat = "Identity")+theme_minimal()+theme(legend.position="",axis.text.x=element_text(angle=90, hjust=1))+labs(x="Country Name",y="Trust or Corruption")

Analysis of SAARC Region

#happy_2017[happy_2017$Region=="Southern Asia",]
saarc <- happy_2017%>% filter(Region=="Southern Asia")

saarc$Country <- as.character(saarc$Country)

cat("Poor Country in Saarc:",saarc$Country[which.min(saarc$Economy..GDP.per.Capita.)])

## Poor Country in Saarc: Afghanistan

cat("\nRich Country in Saarc:",saarc$Country[which.max(saarc$Economy..GDP.per.Capita.)])

## 
## Rich Country in Saarc: Sri Lanka

ggplot(saarc,aes(x=reorder(Country,Economy..GDP.per.Capita.),y=Economy..GDP.per.Capita.,fill=Country))+geom_col()+labs(title="Gdp per capita of SAARC Country",x="",y="GDP Per Capita")+theme_minimal()+theme(legend.position = "")

head(saarc)

ggplot(arrange(saarc,Health..Life.Expectancy.),aes(x=reorder(Country,Health..Life.Expectancy.),y=Health..Life.Expectancy.,fill=Country))+ geom_col()+labs(title="Life Expectancy in SAARC Country",x="",y="Life Expectancy")+theme_minimal()+theme(legend.position = "")

ggplot(arrange(saarc,Trust..Government.Corruption.),aes(x=reorder(Country,Trust..Government.Corruption.),y=Trust..Government.Corruption.,fill=Country))+ geom_col()+labs(title="Trust for Government in SAARC Country",x="",y="Trust")+theme_minimal()+theme(legend.position = "")

ggplot(arrange(saarc,Generosity),aes(x=reorder(Country,Generosity),y=Generosity,fill=Country))+ geom_col()+labs(title="Generosity in SAARC Country",x="",y="Generosity")+theme_minimal()+theme(legend.position = "")

ggplot(arrange(saarc,Freedom),aes(x=reorder(Country,Freedom),y=Freedom,fill=Country))+ geom_col()+labs(title="Freedom in SAARC Country",x="",y="Freedom")+theme_minimal()+theme(legend.position = "")

ggplot(arrange(saarc,Happiness.Score),aes(x=reorder(Country,Happiness.Score),y=Happiness.Score,fill=Country))+ geom_col()+labs(title="Happiness in SAARC Country",x="",y="Happiness Score")+theme_minimal()+theme(legend.position = "")

ggplot(arrange(saarc,Happiness.Rank),aes(x=reorder(Country,Happiness.Rank),y=Happiness.Rank,fill=Country))+ geom_col()+labs(title="Happiness Rank in SAARC Country",x="",y="Happiness Rank")+theme_minimal()+theme(legend.position = "")+geom_text(aes(label = round(Happiness.Rank, 2)), position = position_stack(vjust = 0.5), size = 3)

World Happiness Report Analysis