Introduction to GGPlot 2

2.1 A worked example

data(CPS85 , package = "mosaicData")

2.1.1 ggplot

library(ggplot2)
ggplot(data = CPS85,
       mapping = aes(x = exper, y = wage))

2.1.2 geoms

ggplot(data = CPS85,
       mapping = aes(x = exper, y = wage)) +
  geom_point()

library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

plotdata <- filter(CPS85, wage < 40)
ggplot(data = plotdata,
       mapping = aes(x = exper, y = wage)) +
  geom_point()

ggplot(data = plotdata,
       mapping = aes(x = exper, y = wage)) +
  geom_point(color = "cornflowerblue",
             alpha = .7,
             size = 3)

ggplot(data = plotdata,
       mapping = aes(x = exper, y = wage)) +
  geom_point(color = "cornflowerblue",
             alpha = .7,
             size = 3) +
  geom_smooth(method = "lm")

2.1.3 grouping

ggplot(data = plotdata,
       mapping = aes(x = exper, 
                     y = wage,
                     color = sex)) +
  geom_point(alpha = .7,
             size = 3) +
  geom_smooth(method = "lm", 
              se = FALSE, 
              size = 1.5)

2.1.4 scales

ggplot(data = plotdata,
       mapping = aes(x = exper, 
                     y = wage,
                     color = sex)) +
  geom_point(alpha = .7,
             size = 3) +
  geom_smooth(method = "lm", 
              se = FALSE, 
              size = 1.5) +
  scale_x_continuous(breaks = seq(0, 60, 10)) +
  scale_y_continuous(breaks = seq(0, 30, 5),
                     label = scales::dollar) +
  scale_color_manual(values = c("indianred3", 
                                "cornflowerblue"))

2.1.5 facets

ggplot(data = plotdata,
       mapping = aes(x = exper, 
                     y = wage,
                     color = sex)) +
  geom_point(alpha = .7) +
  geom_smooth(method = "lm", 
              se = FALSE) +
  scale_x_continuous(breaks = seq(0, 60, 10)) +
  scale_y_continuous(breaks = seq(0, 30, 5),
                     label = scales::dollar) +
  scale_color_manual(values = c("indianred3", 
                                "cornflowerblue")) +
  facet_wrap(~sector)

2.1.6 labels

ggplot(data = plotdata,
       mapping = aes(x = exper, 
                     y = wage,
                     color = sex)) +
  geom_point(alpha = .7) +
  geom_smooth(method = "lm", 
              se = FALSE) +
  scale_x_continuous(breaks = seq(0, 60, 10)) +
  scale_y_continuous(breaks = seq(0, 30, 5),
                     label = scales::dollar) +
  scale_color_manual(values = c("indianred3", 
                                "cornflowerblue")) +
  facet_wrap(~sector) +
  labs(title = "Relationship between wages and experience",
       subtitle = "Current Population Survey",
       caption = "source: http://mosaic-web.org/",
       x = " Years of Experience",
       y = "Hourly Wage",
       color = "Gender")

2.1.7 themes

ggplot(data = plotdata,
       mapping = aes(x = exper, 
                     y = wage,
                     color = sex)) +
  geom_point(alpha = .6) +
  geom_smooth(method = "lm", 
              se = FALSE) +
  scale_x_continuous(breaks = seq(0, 60, 10)) +
  scale_y_continuous(breaks = seq(0, 30, 5),
                     label = scales::dollar) +
  scale_color_manual(values = c("indianred3", 
                                "cornflowerblue")) +
  facet_wrap(~sector) +
  labs(title = "Relationship between wages and experience",
       subtitle = "Current Population Survey",
       caption = "source: http://mosaic-web.org/",
       x = " Years of Experience",
       y = "Hourly Wage",
       color = "Gender") +
  theme_minimal()