Chapter 4 Methods

We describe our methods in this chapter.

library(ggplot2)
library(gcookbook)
library(RColorBrewer)

문제 1

ggplot(data=mpg, mapping = 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`.

문제 2

ggplot(data = mpg, mapping = 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`.

문제 3

options(scipen=999)
ggplot(data=midwest, mapping = 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).

문제 4

ggplot(data = iris, mapping = aes(x = Sepal.Length, y = Sepal.Width, shape = Species)) +
  geom_point(alpha = 0.5, size = 6, aes(color = Species)) +
  labs(title = "Scatterplot", 
       subtitle = "Sepal.Length Vs Sepal.Width",
       caption = "Source: iris") +
  theme_minimal()

문제 5

ggplot(data=heightweight, mapping = 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'

문제 6

ggplot(data = mpg, mapping = aes(x = manufacturer, fill = class)) +
  geom_bar(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))