10  scale()

10.1 公共参数

公共参数name,breaks,labels,limits

10.1.1 离散型 例 1

── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
✔ ggplot2 3.3.6      ✔ purrr   0.3.5 
✔ tibble  3.1.8      ✔ dplyr   1.0.10
✔ tidyr   1.2.1      ✔ stringr 1.4.1 
✔ readr   2.1.3      ✔ forcats 0.5.2 
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
p0 <- ggplot(mpg, aes(class))+geom_bar(aes(fill=drv));p0

#更改图例名字 #
p0 + scale_fill_discrete(name="class") 

# 对应指定并更改图例标签 #
p0 + scale_fill_discrete (breaks = c("4", "r", "f"), 
                          labels = c("four", "rr", "rr"))

# 只显示4和r对应部分# 
p0 + scale_fill_discrete (limits=c("4", "r")) 

# 多出一个分类#
p0 + scale_fill_discrete (limits=c("4", "r", "f", "6"))

10.1.2 离散型 例 2

p1 <- ggplot(mtcars, aes(factor(cyl), mpg)) + geom_point();p1

p1 + scale_x_discrete(name="cyl") 

p1 + scale_x_discrete(labels = c("4"="a","6"="b","8"="c")) 

p1 + scale_x_discrete(labels = letters[1:3],breaks=c("4","6","8")) 

p1 + scale_x_discrete(labels = c("4"="a","6"="b"))

p1 + scale_x_discrete(labels = letters[1:3])

p1 + scale_x_discrete(limits=c("4","6"))
Warning: Removed 14 rows containing missing values (geom_point).

10.1.3 连续型 例 1

p2<-ggplot(mpg,aes(displ, hwy , color = cyl))+geom_point();p2

p2 +scale_color_continuous (name="Cyl",
                            breaks=c(7.5,6.2,4.9),
                            labels=c("a","b","c"))

p2 +scale_color_continuous (name="CYL",
                            limits=c(5,6.8))

10.1.4 连续型 例 2

p3 <- ggplot(mtcars, aes(factor(cyl), mpg)) + geom_point();p3

p3 + scale_y_continuous("ylab_mpg")

p3 + scale_y_continuous(breaks = c(10,20,30))

p3 + scale_y_continuous(breaks = c(10,20,30), labels=scales::dollar)

p3 + scale_y_continuous(limits = c(10,30))
Warning: Removed 4 rows containing missing values (geom_point).

p3 + scale_y_reverse() # 纵坐标翻转，小数在上面，大数在下面#

p3 + scale_y_continuous(trans = "log10")

10.2 更改颜色

更改color/fill

10.2.1 离散型 例 1

p0 <- ggplot(mpg, aes(class))+geom_bar(aes(fill=drv));p0 

p0 + scale_fill_manual(values=c("red", "blue", "green")) # 直接指定三个颜色# 

p0 + scale_color_hue(h=c(15,100)) #前面使用fill分组，用color系列无效#

p0 + scale_fill_brewer(palette = "Greens",direction = -1)

p0 + scale_fill_grey(start=1, end=0.5)#0为黑，1为白#

10.2.2 离散型 例 2

x <- sample(LETTERS,13); y <- 1:13
x
 [1] "L" "N" "H" "V" "M" "Z" "D" "W" "E" "K" "B" "Q" "G"
y
 [1]  1  2  3  4  5  6  7  8  9 10 11 12 13
p<-ggplot()+geom_col(data=NULL,aes(x,y,fill=x));p

Warning in RColorBrewer::brewer.pal(n, pal): n too large, allowed maximum for palette Blues is 9
Returning the palette you asked for with that many colors

p+scale_fill_brewer(palette="YlOrRd")
Warning in RColorBrewer::brewer.pal(n, pal): n too large, allowed maximum for palette YlOrRd is 9
Returning the palette you asked for with that many colors

x<-x[1:8];y<-y[1:8]
x
[1] "L" "N" "H" "V" "M" "Z" "D" "W"
y
[1] 1 2 3 4 5 6 7 8
p<-ggplot()+geom_col(data=NULL,aes(x,y,fill=x));p

p+scale_fill_brewer(palette="YlOrRd")

10.2.3 连续型 例 1

p1<-ggplot(mpg,aes(displ, hwy , color = cyl))+geom_point();p1

p1 + scale_color_gradient2(low = "white", mid = "red", high = "black") 

p1 + scale_color_distiller(palette = "Spectral")

10.2.4 连续型 例 2

p<-ggplot(faithfuld, aes(waiting, eruptions)) + geom_raster(aes(fill = density));p

max(faithfuld$density);min(faithfuld$density)  
[1] 0.0369878
[1] 1.25925e-24
p + scale_fill_gradient(limits=c(0.001,0.004))   

p + scale_fill_gradient(low = 'blue', high = 'red')

p + scale_fill_gradient2(low = 'blue', high = 'red')  

p + scale_fill_gradient2(low = 'blue', high = 'red', midpoint = 0.02)

p + scale_fill_gradientn(colours = c('black','blue','red','white'))  

p + scale_fill_gradientn(colours = topo.colors(10))  

p + scale_fill_gradientn(colours = cm.colors(10))

p + scale_fill_distiller(palette = "Spectral")

10.3 scale_color_identity()

pp1<-ggplot(mpg,aes(displ, hwy , color = "blue"))+geom_point();pp1

col <- c("red","yellow","blue","black")
val <- abs(rnorm(4))*10;val
[1]  7.497713  5.036814 14.489637  7.368140
data<-data.frame("col"=col,"val"=val)
data
     col       val
1    red  7.497713
2 yellow  5.036814
3   blue 14.489637
4  black  7.368140
pp2<-ggplot(data,aes(x=col,y=val,fill=col))+geom_col();pp2

10.4 scale_shape_**()

df_shapes <- data.frame(shape = 0:24)
df_shapes
   shape
1      0
2      1
3      2
4      3
5      4
6      5
7      6
8      7
9      8
10     9
11    10
12    11
13    12
14    13
15    14
16    15
17    16
18    17
19    18
20    19
21    20
22    21
23    22
24    23
25    24
ggplot(df_shapes, aes(0, 0, shape = shape)) +
  geom_point(aes(shape = shape), size = 5, fill = 'red') +
  scale_shape_identity() +
  facet_wrap(~shape)

p<-ggplot(mpg)+
   geom_point(aes(cty, hwy, shape = manufacturer));p
Warning: The shape palette can deal with a maximum of 6 discrete values because
more than 6 becomes difficult to discriminate; you have 15. Consider
specifying shapes manually if you must have them.
Warning: Removed 112 rows containing missing values (geom_point).

p+ scale_shape_manual(values=seq(1,15,1))

10.5 scale_linetype_**()

df_lines <- data.frame(
    linetype = factor(
        1:4,
        labels = c("solid", "longdash", "dashed", "dotted")
    )
)
df_lines
  linetype
1    solid
2 longdash
3   dashed
4   dotted
ggplot(df_lines) +
    geom_hline(aes(linetype = linetype, yintercept = 0), size = 2) +
    scale_linetype_identity() +
    facet_grid(linetype ~ .) 

df_lines <- data.frame(
    linetype = factor(
        1:13,
        labels = as.character(seq(0,12,1))
    )
)
ggplot(df_lines) +
    geom_hline(aes(linetype = linetype, yintercept = 0), size = 2) +
    facet_grid(linetype ~ .)

10.6 scale_size_**()

p<-ggplot(mpg)+
   geom_point(aes(displ, hwy, size = hwy),alpha=0.2);p

p+scale_size(range=c(0,10))

p+scale_size_area(max_size=10)

p+scale_radius(range=c(0,10))