library(ggplot2)

Problem 1

ggplot(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(mpg, aes(x = hwy, fill = drv)) +
  geom_histogram(alpha = 0.5) +
  labs(title = "Histogram", subtitle = "Histogram of Highway Mile Per Gallon", caption = "Source: mpg") + facet_grid(rows = vars(drv)) + theme_minimal()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

Problem 3

library(ggplot2)
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'

Problem 4

ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width, color = Species, shape = Species)) +
  geom_point(alpha = 0.5, size = 6) + 
  labs(title = "Scatterplot", 
       subtitle = "Sepal.Length Vs Sepal.Width", 
       caption = "Source: iris", 
       x = "Sepal.Length", 
       y = "Sepal.Width") + theme_minimal() + scale_color_manual(name = "Species", values = c("lightpink", "lightgreen", "lightblue"))

library(gcookbook)

Problem 5

ggplot(heightweight, aes(x = heightIn, y = weightLb, color = sex)) + geom_point(size = 3, alpha = 0.5) + geom_smooth(method = lm, se=FALSE) + labs(title = "Scatterplot", 
       subtitle = "Weight Vs Height", 
       caption = "Source: heightweight", 
       x = "heightIn", 
       y = "weightLb") + theme_classic()
## `geom_smooth()` using formula 'y ~ x'

Problem 6

library(gcookbook)
library(RColorBrewer)
ggplot(data=mpg, aes(x = manufacturer)) + geom_bar(aes(fill=class), width=0.5) + scale_fill_brewer(palette="Spectral") +
  labs(title="Barplot",
       subtitle="Manufacturer across Vehicle Classes") + theme_minimal() + theme(axis.text.x=element_text(angle=65))