data <- read.csv("alldataset_delTW.csv") %>% 
  dplyr::select(Year, CountryName, Emissions, Percentage_of_individuals, Happiness_Score, Economy, Family, Health, Freedom, Trust, 
                Generosity, Number_of_incident_tuberculosis, GDP, Unemployment, Total_Population, langoff_1, HDI)
data$Year = factor(data$Year)

Year / Emissions

data %>% 
  ggplot(aes(Year, Emissions, group = Year)) +
  geom_boxplot() +
  theme(text = element_text(size=10), axis.text.x = element_text(vjust = 0.5, hjust = 0.5, angle = 90))

Year / Percentage_of_individuals

data %>% 
  ggplot(aes(Year, Percentage_of_individuals, group = Year)) +
  geom_boxplot() +
  theme(text = element_text(size=10), axis.text.x = element_text(vjust = 0.5, hjust = 0.5, angle = 90))

Year / Happiness_Score

data %>% 
  ggplot(aes(Year, Happiness_Score, group = Year)) +
  geom_boxplot() +
  theme(text = element_text(size=10), axis.text.x = element_text(vjust = 0.5, hjust = 0.5, angle = 90))

Year / Economy

data %>% 
  ggplot(aes(Year, Economy, group = Year)) +
  geom_boxplot() +
  theme(text = element_text(size=10), axis.text.x = element_text(vjust = 0.5, hjust = 0.5, angle = 90))

Year / Family

data %>% 
  ggplot(aes(Year, Family, group = Year)) +
  geom_boxplot() +
  theme(text = element_text(size=10), axis.text.x = element_text(vjust = 0.5, hjust = 0.5, angle = 90))

Year / Health

data %>% 
  ggplot(aes(Year, Health, group = Year)) +
  geom_boxplot() +
  theme(text = element_text(size=10), axis.text.x = element_text(vjust = 0.5, hjust = 0.5, angle = 90))

Year / Freedom

data %>% 
  ggplot(aes(Year, Freedom, group = Year)) +
  geom_boxplot() +
  theme(text = element_text(size=10), axis.text.x = element_text(vjust = 0.5, hjust = 0.5, angle = 90))

Year / Trust

data %>% 
  ggplot(aes(Year, Trust, group = Year)) +
  geom_boxplot() +
  theme(text = element_text(size=10), axis.text.x = element_text(vjust = 0.5, hjust = 0.5, angle = 90))

Year / Generosity

data %>% 
  ggplot(aes(Year, Generosity, group = Year)) +
  geom_boxplot() +
  theme(text = element_text(size=10), axis.text.x = element_text(vjust = 0.5, hjust = 0.5, angle = 90))

Year / Number_of_incident_tuberculosis

data %>% 
  ggplot(aes(Year, Number_of_incident_tuberculosis, group = Year)) +
  geom_boxplot() +
  theme(text = element_text(size=10), axis.text.x = element_text(vjust = 0.5, hjust = 0.5, angle = 90))

## Warning: Removed 3 rows containing non-finite values (stat_boxplot).

Year / GDP

data %>% 
  ggplot(aes(Year, GDP, group = Year)) +
  geom_boxplot() +
  theme(text = element_text(size=10), axis.text.x = element_text(vjust = 0.5, hjust = 0.5, angle = 90))

## Warning: Removed 1 rows containing non-finite values (stat_boxplot).

Year / Unemployment

data %>% 
  ggplot(aes(Year, Unemployment, group = Year)) +
  geom_boxplot() +
  theme(text = element_text(size=10), axis.text.x = element_text(vjust = 0.5, hjust = 0.5, angle = 90))

Year / Total_Population

data %>% 
  ggplot(aes(Year, Total_Population, group = Year)) +
  geom_boxplot() +
  theme(text = element_text(size=10), axis.text.x = element_text(vjust = 0.5, hjust = 0.5, angle = 90))

Year / HDI

data %>% 
  ggplot(aes(Year, HDI, group = Year)) +
  geom_boxplot() +
  theme(text = element_text(size=10), axis.text.x = element_text(vjust = 0.5, hjust = 0.5, angle = 90))

Country / langoff_1

data %>% 
  filter(Year == 2017) %>% 
  group_by(langoff_1) %>% 
  summarise(n = n(), .groups = 'drop') %>%
  mutate(langoff_1 = reorder(langoff_1, -n)) %>% 
  ggplot(aes(langoff_1, n)) +
  geom_bar(stat = "identity") + 
  theme(text = element_text(size=12), axis.text.x = element_text(vjust = 0.9, hjust = 1, angle = 45))

CountryName / Percentage_of_individuals

# 以國家為X軸效果不太好
ggplot(data, aes(CountryName, Percentage_of_individuals)) +
  geom_boxplot()+
  theme(text = element_text(size=10), axis.text.x = element_text(vjust = 0.5, hjust = 0.5, angle = 90))

分出國家

Year / Emissions

data %>% 
  ggplot(aes(Year, Emissions, group=CountryName)) +
  geom_line(aes(color=CountryName))

Year / Percentage_of_individuals

data %>% 
  ggplot(aes(Year, Percentage_of_individuals, group=CountryName)) +
  geom_line(aes(color=CountryName))

Year / Happiness_Score

data %>% 
  ggplot(aes(Year, Happiness_Score, group=CountryName)) +
  geom_line(aes(color=CountryName))

Year / Economy

data %>% 
  ggplot(aes(Year, Economy, group=CountryName)) +
  geom_line(aes(color=CountryName))

Year / Family

data %>% 
  ggplot(aes(Year, Family, group=CountryName)) +
  geom_line(aes(color=CountryName))

Year / Health

data %>% 
  ggplot(aes(Year, Health, group=CountryName)) +
  geom_line(aes(color=CountryName))

Year / Freedom

data %>% 
  ggplot(aes(Year, Freedom, group=CountryName)) +
  geom_line(aes(color=CountryName))

Year / Trust

data %>% 
  ggplot(aes(Year, Trust, group=CountryName)) +
  geom_line(aes(color=CountryName))

Year / Generosity

data %>% 
  ggplot(aes(Year, Generosity, group=CountryName)) +
  geom_line(aes(color=CountryName))

Year / Number_of_incident_tuberculosis

data %>% 
  ggplot(aes(Year, Number_of_incident_tuberculosis, group=CountryName)) +
  geom_line(aes(color=CountryName))

## Warning: Removed 3 rows containing missing values (geom_path).

Year / GDP

data %>% 
  ggplot(aes(Year, GDP, group=CountryName)) +
  geom_line(aes(color=CountryName))

## Warning: Removed 1 rows containing missing values (geom_path).

Year / Unemployment

data %>% 
  ggplot(aes(Year, Unemployment, group=CountryName)) +
  geom_line(aes(color=CountryName))

Year / Total_Population

data %>% 
  ggplot(aes(Year, Total_Population, group=CountryName)) +
  geom_line(aes(color=CountryName))

Year / HDI

data %>% 
  ggplot(aes(Year, HDI, group=CountryName)) +
  geom_line(aes(color=CountryName))