Problem 1
library(ggplot2)
ggplot(data=mpg, aes(x=hwy, fill=drv))+geom_histogram(alpha=0.5)+
labs(title="Histogram",
subtitle="Histogram of Highway Mile Per Gallon",
caption="Source: mpg")+theme_minimal()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Problem 2
ggplot(data=mpg, aes(x=hwy, fill=drv))+geom_histogram(alpha=0.5)+facet_grid(rows=vars(drv))+
labs(title="Histogram using facet_grid()",
subtitle="Histogram of Highway Mile Per Gallon",
caption="Source: mpg")+theme_minimal()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Problem 3
options(scipen = 999)
ggplot(data=midwest, aes(x=area, y=poptotal))+geom_point(aes(color=state, size=popdensity), alpha=0.4)+geom_smooth(se=FALSE)+scale_x_continuous(limits=c(0,0.1))+scale_y_continuous(limits = c(0,500000))+
labs(title = "Scatterplot",
subtitle="Area Vs Population",
caption="Source:midwest",
y="population")+theme_classic()
## `geom_smooth()` using method = 'loess' and formula 'y ~ x'
## Warning: Removed 15 rows containing non-finite values (stat_smooth).
## Warning: Removed 15 rows containing missing values (geom_point).
Problem 4
ggplot(data=iris, aes(x=Sepal.Length, y=Sepal.Width))+geom_point(aes(shape=Species, color=Species), alpha=0.5, size=6)+
labs(title="Scatterplot",
subtitle="Sepal.Length Vs Sepal.Width",
caption="Source:iris")+theme_minimal()
Problem 5
library(gcookbook)
ggplot(data=heightweight, aes(x=heightIn, y=weightLb,color=sex))+geom_point(alpha=0.5, size=3)+geom_smooth(method=lm, se=FALSE)+
labs(title = "Scatterplot",
subtitle="weight Vs Height",
caption="Source:heightweight")+theme_classic()
## `geom_smooth()` using formula 'y ~ x'
