ggplot2: Scales

library(ggplot2)
plot <- qplot(cty, hwy, data = mpg)

## Error: ggplot2 doesn't know how to deal with data of class numeric

plot

## standardGeneric for "plot" defined from package "graphics"
## 
## function (x, y, ...) 
## standardGeneric("plot")
## <environment: 0x46d7a88>
## Methods may be defined for arguments: x, y
## Use  showMethods("plot")  for currently available ones.

plot + aes(x = drv)

## Error in plot + aes(x = drv): non-numeric argument to binary operator

p <- qplot(sleep_total, sleep_cycle, data = msleep, colour = vore)
p 

## Warning: Removed 51 rows containing missing values (geom_point).

# Explicitly add the default scale
p + scale_colour_hue()

## Warning: Removed 51 rows containing missing values (geom_point).

# Adjust parameters of the default, here changing the appearance 
# of the legend
p + scale_colour_hue("What does\nit eat?", 
   breaks = c("herbi", "carni", "omni", NA), 
   labels = c("plants", "meat", "both", "don't know"))

## Warning: Removed 51 rows containing missing values (geom_point).

# Use a different scale
p + scale_colour_brewer(palette = "Set1")

## Warning: Removed 51 rows containing missing values (geom_point).

p <- qplot(cty, hwy, data = mpg, colour = displ)

## Error: ggplot2 doesn't know how to deal with data of class numeric

p

## Warning: Removed 51 rows containing missing values (geom_point).

p + scale_x_continuous("City mpg")

## Warning: Removed 51 rows containing missing values (geom_point).

p + xlab("City mpg")

## Warning: Removed 51 rows containing missing values (geom_point).

p + ylab("Highway mpg")

## Warning: Removed 51 rows containing missing values (geom_point).

p + labs(x = "City mpg", y = "Highway", colour = "Displacement")

## Warning: Removed 51 rows containing missing values (geom_point).

p + xlab(expression(frac(miles, gallon)))

## Warning: Removed 51 rows containing missing values (geom_point).

p <- qplot(cyl, wt, data = mtcars)
p

p + scale_x_continuous(breaks = c(4, 8))

p + scale_x_continuous(limits = c(4, 8))

p <- qplot(wt, cyl, data = mtcars, colour = cyl)
p

p + scale_colour_gradient(breaks = c(5.5, 6.5))

p + scale_colour_gradient(limits = c(5.5, 6.5))

# Khác nhau giữa log scale và log data: tên các trục khác nhau
qplot(log10(carat), log10(price), data = diamonds)

qplot(carat, price, data = diamonds) + 
  scale_x_log10() + scale_y_log10()

plot <- qplot(date, psavert, data = economics, geom = "line") + 
  ylab("Personal savings rate") +
  geom_hline(xintercept = 0, colour = "grey50")
plot

# Cần thêm thư viện 'scales'
library(scales)
plot + scale_x_date(breaks = date_breaks("10 years"))

plot + scale_x_date(
  limits = as.Date(c("2004-01-01", "2005-01-01")),
  labels = date_format("%Y-%m-%d")
)

# gradient và gradient2
f2d <- with(faithful, MASS::kde2d(eruptions, waiting, 
  h = c(1, 10), n = 50))
df <- with(f2d, cbind(expand.grid(x, y), as.vector(z)))
names(df) <- c("eruptions", "waiting", "density")
erupt <- ggplot(df, aes(waiting, eruptions, fill = density)) +
  geom_tile() +
  scale_x_continuous(expand = c(0, 0)) + 
  scale_y_continuous(expand = c(0, 0))
erupt + scale_fill_gradient(limits = c(0, 0.04))

erupt + scale_fill_gradient(limits = c(0, 0.04), 
  low = "white", high = "black") 

erupt + scale_fill_gradient2(limits = c(-0.04, 0.04), 
  midpoint = mean(df$density)) 

# gradientn
library(vcd)

## Error in library(vcd): there is no package called 'vcd'

fill_gradn <- function(pal) {
  scale_fill_gradientn(colours = pal(7), limits = c(0, 0.04))
}
# Tải thêm thư viện `colorspace`
library(colorspace)
erupt + fill_gradn(rainbow_hcl)

erupt + fill_gradn(diverge_hcl)

erupt + fill_gradn(heat_hcl)

# 3 ColorBrewer palettes
point <- qplot(brainwt, bodywt, data = msleep, log = "xy", 
  colour = vore)
area <- qplot(log10(brainwt), data = msleep, fill = vore, 
  binwidth = 1)
# Chú ý 'pal=' không làm việc, phải dùng 'palette=', không hiểu
# tại sao.
point + scale_colour_brewer(palette = "Set1")

## Warning: Removed 27 rows containing missing values (geom_point).

point + scale_colour_brewer(palette = "Set2")

## Warning: Removed 27 rows containing missing values (geom_point).

point + scale_colour_brewer(palette = "Pastel1")

## Warning: Removed 27 rows containing missing values (geom_point).

area + scale_fill_brewer(palette = "Set1")

area + scale_fill_brewer(palette = "Set2")

area + scale_fill_brewer(palette = "Pastel1")

# Màu tùy chỉnh
plot <- qplot(brainwt, bodywt, data = msleep, log = "xy")
plot + aes(colour = vore) + 
  scale_colour_manual(values = c("red", "orange", "yellow", 
    "green", "blue"))

## Warning: Removed 27 rows containing missing values (geom_point).

colours <- c(carni = "red", "NA" = "orange", insecti = "yellow", 
  herbi = "green", omni = "blue")
plot + aes(colour = vore) + scale_colour_manual(values = colours)

## Warning: Removed 27 rows containing missing values (geom_point).

# Hình dạng tùy chỉnh
plot + aes(shape = vore) + 
  scale_shape_manual(values = c(1, 2, 6, 0, 23))

## Warning: Removed 32 rows containing missing values (geom_point).

# Đa màu sắc
huron <- data.frame(year = 1875:1972, level = LakeHuron)
ggplot(huron, aes(year)) +
  geom_line(aes(y = level - 5), colour = "blue") + 
  geom_line(aes(y = level + 5), colour = "red")

## Don't know how to automatically pick scale for object of type ts. Defaulting to continuous

ggplot(huron, aes(year)) +
  geom_line(aes(y = level - 5, colour = "below")) + 
  geom_line(aes(y = level + 5, colour = "above"))

## Don't know how to automatically pick scale for object of type ts. Defaulting to continuous

ggplot(huron, aes(year)) +
  geom_line(aes(y = level - 5, colour = "below")) + 
  geom_line(aes(y = level + 5, colour = "above")) + 
  scale_colour_manual("Direction", 
    values = c("below" = "blue", "above" = "red"))

## Don't know how to automatically pick scale for object of type ts. Defaulting to continuous

x <- colors()
luv <- as.data.frame(convertColor(t(col2rgb(x)), "sRGB", "Luv"))
qplot(u, v, data=luv, colour = x, size = I(3)) + scale_colour_identity() +
   coord_equal()

# Legends produced by geom: point, line, point and line, and bar.
p <- ggplot(diamonds[1:100, ], aes(price, carat, colour = cut))
p + geom_point()

p + geom_line()

p + geom_point() + geom_line()

p + geom_bar(binwidth = 100) + aes(fill = cut, y = ..count..)

# Colour legend, shape legend, colour + shape legend.
p <- ggplot(diamonds[1:100, ], aes(price, carat)) +  
  geom_point()
p + aes(colour = cut)

p + aes(shape = cut)

p + aes(shape = cut, colour = cut)