Data Preprocessing
data15 <- read.csv("C:/Users/power/BST260/Project/world-happiness/world-happiness-new/2015.csv", stringsAsFactors = F)
data16 <- read.csv("C:/Users/power/BST260/Project/world-happiness/world-happiness-new/2016.csv", stringsAsFactors = F)
data17 <- read.csv("C:/Users/power/BST260/Project/world-happiness/world-happiness-new/2017.csv", stringsAsFactors = F)
#Data Process. Adding continents
data15$continent <- NA
data15$continent[which(data15$Region %in% c("Eastern Asia", "Southeastern Asia", "Southern Asia"))] <- "Asia"
data15$continent[which(data15$Region %in% c("Central and Eastern Europe", "Western Europe"))] <- "Europe"
data15$continent[which(data15$Region == "North America")] <- "North America"
data15$continent[which(data15$Country %in% c("Canada", "Jamaica", "Honduras", "Trinidad and Tobago",
"Panama", "El Salvador","Haiti", "Peru",
"Costa Rica", "Dominican Republic", "Mexico", "United States",
"Guatemala", "Nicaragua"))] <- "North America"
data15$continent[which(data15$Country %in% c("Brazil", "Chile", "Argentina", "Uruguay",
"Colombia", "Ecuador","Paraguay", "Peru",
"Bolivia", "Venezuela", "Suriname"))] <- "South America"
data15$continent[which(data15$Country %in% c("United Arab Emirates", "Oman", "Qatar", "Saudi Arabia",
"Kuwait", "Bahrain","Libya", "Jordan",
"Lebanon", "Iraq", "Iran", "Yemen", "Syria",
"Turkey", "Israel", "Egypt", "Palestinian Territories"))] <- "Middle East"
data15$continent[which(data15$Country %in% c("Mauritius", "Nigeria", "Zambia", "Somaliland region",
"Mozambique", "Lesotho","Swaziland", "South Africa",
"Ghana", "Zimbabwe", "Tunisia", "Morocco", "Algeria",
"Sudan", "Congo (Kinshasa)", "Liberia",
"Ethiopia", "Sierra Leone", "Mauritania", "Kenya", "Djibouti",
"Botswana", "Malawi", "Cameroon", "Angola",
"Mali", "Congo (Brazzaville)", "Comoros", "Uganda",
"Senegal", "Gabon", "Niger", "Tanzania", "Madagascar",
"Central African Republic", "Chad", "Guinea",
"Ivory Coast", "Burkina Faso", "Rwanda",
"Benin", "Burundi", "Togo", "Namibia"))] <- "Africa"
data15$continent[which(data15$Country %in% c("Australia", "New Zealand"))] <- "Oceania"
data16$continent <- NA
data16$continent[which(data16$Region %in% c("Eastern Asia", "Southeastern Asia", "Southern Asia"))] <- "Asia"
data16$continent[which(data16$Region %in% c("Central and Eastern Europe", "Western Europe"))] <- "Europe"
data16$continent[which(data16$Region == "North America")] <- "North America"
data16$continent[which(data16$Country %in% c("Canada", "Jamaica", "Honduras", "Trinidad and Tobago",
"Panama", "El Salvador","Haiti", "Peru",
"Costa Rica", "Dominican Republic", "Mexico", "United States",
"Guatemala", "Nicaragua", "Puerto Rico", "Belize"))] <- "North America"
data16$continent[which(data16$Country %in% c("Brazil", "Chile", "Argentina", "Uruguay",
"Colombia", "Ecuador","Paraguay", "Peru",
"Bolivia", "Venezuela", "Suriname"))] <- "South America"
data16$continent[which(data16$Country %in% c("United Arab Emirates", "Oman", "Qatar", "Saudi Arabia",
"Kuwait", "Bahrain","Libya", "Jordan",
"Lebanon", "Iraq", "Iran", "Yemen", "Syria",
"Turkey", "Israel", "Egypt", "Palestinian Territories"))] <- "Middle East"
data16$continent[which(data16$Country %in% c("Mauritius", "Nigeria", "Zambia", "Somaliland region",
"Mozambique", "Lesotho","Swaziland", "South Africa",
"Ghana", "Zimbabwe", "Tunisia", "Morocco", "Algeria",
"Sudan", "Congo (Kinshasa)", "Liberia",
"Ethiopia", "Sierra Leone", "Mauritania", "Kenya", "Djibouti",
"Botswana", "Malawi", "Cameroon", "Angola",
"Mali", "Congo (Brazzaville)", "Comoros", "Uganda",
"Senegal", "Gabon", "Niger", "Tanzania", "Madagascar",
"Central African Republic", "Chad", "Guinea",
"Ivory Coast", "Burkina Faso", "Rwanda",
"Benin", "Burundi", "Togo", "Namibia", "Somaliland Region",
"South Sudan", "Somalia"))] <- "Africa"
data16$continent[which(data16$Country %in% c("Australia", "New Zealand"))] <- "Oceania"
Happiness around the world
newdata15 <- data15[,c("Country","Happiness.Score")]
newdata15$Country <- as.character(data15$Country)
colnames(newdata15)<-c("country","value")
Countryname15 <-c("Congo (Brazzaville)"="Democratic Republic of the Congo","Guinea"="Equatorial Guinea",
"North Cyprus"="Northern Cyprus","Serbia"="Republic of Serbia",
"Congo (Brazzaville)"="Republic of Congo",
"Tanzania"="United Republic of Tanzania","United States Minor Outlying Islands"="United States",
"United States"="United States of America","United States"="United States Virgin Islands")
for(i in names(Countryname15)){
newdata15[newdata15$country==i,"country"] <- Countryname15[i]
}
hc15 <- highchart() %>%
hc_add_series_map(worldgeojson, newdata15, value = "value", joinBy = c('name','country')) %>%
hc_colorAxis(stops = color_stops()) %>%
#hc_colorAxis(dataClasses = color_classes(c(seq(0, 10, by = 2), 50)))%>%
hc_title(text = "Happiness Score") %>%
hc_subtitle(text = "2015") %>%
hc_tooltip(borderWidth = 1.5, headerFormat = "", valueSuffix = "value")
newdata16 <- data16[,c("Country","Happiness.Score")]
newdata16$Country <- as.character(newdata16$Country)
colnames(newdata16)<-c("country","value")
Countryname16<-c("Congo (Brazzaville)"="Democratic Republic of the Congo","Guinea"="Equatorial Guinea",
"North Cyprus"="Northern Cyprus","Serbia"="Republic of Serbia",
"Congo (Brazzaville)"="Republic of Congo","Somaliland region"="Somaliland",
"Tanzania"="United Republic of Tanzania","United States Minor Outlying Islands"="United States",
"United States"="United States of America","United States"="United States Virgin Islands",
"Somaliland Region"="Somaliland")
for(i in names(Countryname16)){
newdata16[newdata16$country==i,"country"]<-Countryname16[i]
}
hc16 <- highchart() %>%
hc_add_series_map(worldgeojson, newdata16, value = "value", joinBy = c('name','country')) %>%
hc_colorAxis(stops = color_stops()) %>%
#hc_colorAxis(dataClasses = color_classes(c(seq(0, 10, by = 2), 50)))%>%
hc_title(text = "Happiness Score") %>%
hc_subtitle(text = "2016") %>%
hc_tooltip(borderWidth = 1.5, headerFormat = "", valueSuffix = "value")
2015
hc15
- Happiness Score Around the world