4.Density plots

4.1 Basic density

head(df2)

##   sex weight
## 1   F     49
## 2   F     56
## 3   F     60
## 4   F     43
## 5   F     57
## 6   F     58

ggplot(df2, aes(x=weight)) + 
  geom_density()

4.2 Add mean line on a density plot

ggplot(df2, aes(x=weight)) +
  geom_density() +
  geom_vline(aes(xintercept=mean(weight)), color="black", linetype="dashed", size=0.5)

4.3 Change density plot fill colors

#Use the plyr package plyr to calculate the average weight of each group :
mu <- ddply(df2, "sex", summarise, grp.mean=mean(weight))
head(mu)

##   sex grp.mean
## 1   F    54.70
## 2   M    65.36

#draw the plot

4.3.1 Change fill colors

ggplot(df2, aes(x=weight, fill=sex)) +
  geom_density(alpha=0.7)+
  geom_vline(data=mu, aes(xintercept=grp.mean, color=sex), linetype="dashed")+
  labs(title="Weight density curve",x="Weight(kg)", y = "Density") + 
  scale_color_brewer(palette="Paired") +
  scale_fill_brewer(palette="Blues") +
  theme_classic()

4.3.2 Change line colors

ggplot(df2, aes(x=weight, color=sex)) +
  geom_density()+
  geom_vline(data=mu, aes(xintercept=grp.mean, color=sex), linetype="dashed")+
  labs(title="Weight density curve",x="Weight(kg)", y = "Density") + 
  scale_color_brewer(palette="Paired") +
  theme_classic()

4.3.3 Combine histogram and density plots

ggplot(df2, aes(x=weight, color=sex, fill=sex)) + 
  geom_histogram(binwidth=1, aes(y=..density..), alpha=0.5, position="identity") +
  geom_density(alpha=.2) +
  labs(title="Weight density curve",x="Weight(kg)", y = "Density") + 
  scale_color_brewer(palette="Paired") +
  scale_fill_brewer(palette="Blues") +
  theme_classic()

Reference: http://www.sthda.com/english/wiki/ggplot2-density-plot-quick-start-guide-r-software-and-data-visualization