ggplot2学习（5）

> library(ggplot2)
> library(gcookbook)
> BOD
  Time demand
1    1    8.3
2    2   10.3
3    3   19.0
4    4   16.0
5    5   15.6      #数据Time中没有6
6    7   19.8
> ggplot(BOD, aes(Time, demand)) + geom_line()

> ​BOD1 <- BOD  #Make a copy of the data
> ​BOD1$Time <- factor(BOD1$Time)
> ggplot(BOD1, aes(Time, demand)) + geom_line()
geom_path: Each group consists of only one observation. Do you need to adjust the group aesthetic?​
# 因为此时Time为因子型，会有多个分组，如果不加group = 1，使用geom_line()会报错​
​​> ggplot(BOD1, aes(Time, demand, group = 1)) + geom_line()

# 如果是使用 geom_point() 则没问题​
​ggplot(BOD1, aes(Time, demand)) + geom_point()

# 限定y轴范围
ggplot(BOD, aes(Time, demand)) + geom_line() + 
  ylim(0, max(BOD$demand))​

# Adding point to a line graph
ggplot(BOD, aes(Time, demand)) + geom_line() + 
  geom_point(shape = 1, size = 3, aes(colour = factor(Time))) 

> # Making a line graph with multiple lines
> # set a data
> library(plyr)
> tg <- ddply(ToothGrowth, c("supp","dose"), 
 ​             summarise, length = mean(len))
> tg
  supp dose length
1   OJ  0.5  13.23
2   OJ  1.0  22.70
3   OJ  2.0  26.06
4   VC  0.5   7.98
5   VC  1.0  16.77
6   VC  2.0  26.14
> ggplot(tg, aes(dose, length, colour = supp)) + geom_line()

ggplot(tg, aes(dose, length, linetype = supp)) + geom_line()

ggplot(tg, aes(dose, length)) + geom_line()

ggplot(tg, aes(dose, length, fill = supp)) + geom_line() + 
  geom_point(size = 4, shape = 21)

# Changing the appearance of lines
ggplot(BOD, aes(Time, demand)) + 
  geom_line(linetype = "dashed", size =1, colour = "blue")

# Making a graph with a shaded area 即将线图下面区域进行填充
# set a data
sunspotyear <- data.frame(
  Year = as.numeric(time(sunspot.year)),
  Sunspots = as.numeric(sunspot.year)
)

ggplot(sunspotyear, aes(Year, Sunspots)) + geom_line()

ggplot(sunspotyear, aes(Year, Sunspots)) + geom_area()

ggplot(sunspotyear, aes(Year, Sunspots)) +
  geom_area(colour = "black", fill = "blue", alpha = 0.2)

> # Making a stacked area graph
> str(uspopage)
'data.frame':   824 obs. of  3 variables:
 $ Year     : int  1900 1900 1900 1900 1900 1900 1900 1900 1901 1901 ...
 $ AgeGroup : Factor w/ 8 levels "<5","5-14","15-24",..: 1 2 3 4 5 6 7 8 1 2 ...
 $ Thousands: int  9181 16966 14951 12161 9273 6437 4026 3099 9336 17158 ...
> ggplot(uspopage, aes(Year, Thousands)) + geom_area()

ggplot(uspopage, aes(Year, Thousands, fill = AgeGroup)) + geom_area()

ggplot(uspopage, aes(Year, Thousands, fill = AgeGroup)) + 
  geom_area(colour = "black", size = 0.2, alpha = 0.4)

ggplot(uspopage, aes(Year, Thousands, fill = AgeGroup, order = desc(AgeGroup))) + 
  geom_area(colour = "NA", alpha = 0.4) + 
  geom_line(position = "stack", size = 0.2)
# colour = "NA" 图例的区别

> # Making a proportional stacked area graph
> uspopage_prop <- ddply(uspopage, "Year", transform, 
                         Percent = Thousands/sum(Thousands)*100)
> str(uspopage_prop)
'data.frame':  824 obs. of  4 variables:
 $ Year     : int  1900 1900 1900 1900 1900 1900 1900 1900 1901 1901 ...
 $ AgeGroup : Factor w/ 8 levels "<5","5-14","15-24",..: 1 2 3 4 5 6 7 8 1 2 ...
 $ Thousands: int  9181 16966 14951 12161 9273 6437 4026 3099 9336 17158 ...
 $ Percent  : num  12.1 22.3 19.6 16 12.2 ...
> ggplot(uspopage_prop, aes(Year, Percent, fill = AgeGroup)) +
    geom_area(colour = "black", size = .2, alpha = .4)

ggplot(uspopage_prop, aes(Year, Percent, fill = AgeGroup)) +
  geom_area(colour = NA, size = .2, alpha = .4) + 
  geom_line()

ggplot(uspopage_prop, aes(Year, Percent, fill = AgeGroup)) +
  geom_area(colour = NA, size = .2, alpha = .4) + 
  geom_line(position = "stack", size = .2)

> # Adding a confidece region   即上下变动的区间
> clim <- subset(climate, source = "Berkeley",
                 select = c("Year", "Anomaly10y", "Unc10y"))
> clim <- clim[1:205,]
> str(clim)
'data.frame':  205 obs. of  3 variables:
 $ Year      : num  1800 1801 1802 1803 1804 ...
 $ Anomaly10y: num  -0.435 -0.453 -0.46 -0.493 -0.536 -0.541 -0.59 -0.695 -0.763 -0.818 ...
 $ Unc10y    : num  0.505 0.493 0.486 0.489 0.483 0.475 0.468 0.461 0.453 0.451 ...
> ggplot(clim,aes(Year, Anomaly10y)) +
    geom_ribbon(aes(ymin=Anomaly10y-Unc10y, ymax=Anomaly10y+Unc10y), alpha = .2) + 
    geom_line()
# ymin 和 ymax 不可去掉​

# 上图过程等同于
ggplot(clim,aes(Year, Anomaly10y)) +
  geom_line() + #main
  geom_line(aes(x = Year, y = Anomaly10y-Unc10y),
            colour = "grey50", linetype = "dashed") + #lower
  geom_line(aes(x = Year, y = Anomaly10y+Unc10y),
            colour = "grey50", linetype = "dashed")   #upper

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