> library(gcookbook) #for the data set
> pg_mean
group weight
1 ctrl 5.032
2 trt1 4.661
3 trt2 5.526
> ggplot(pg_mean, aes(x=group, y=weight)) + geom_bar(stat = "identity")
# geom_bar() 默认的stat为“bin”， stat=bin则前面aes()中不需要y,会统计x中每一种元素的数目
#stat = "identity"则统计x中每一种元素对应y的数据
ggplot(pg_mean, aes(x=group)) + geom_bar()
# geom_bar() 等同于 geom_bar(stat=“bin”)
>BOD #一个生物需氧量的数据集
Time demand
1 1 8.3
2 2 10.3
3 3 19.0
4 4 16.0
5 5 15.6
6 7 19.8 #注意Time中没有6
>ggplot(BOD, aes(x=Time, y=demand)) + geom_bar(stat = "identity")
ggplot(BOD, aes(x=factor(Time), y=demand)) + geom_bar(stat = "identity")
ggplot(pg_mean, aes(x=group,y=weight)) +
geom_bar(stat = "identity", fill = "lightblue", colour = "black")
> #Grouping bars together
> cabbage_exp
Cultivar Date Weight sd n se
1 c39 d16 3.18 0.9566144 10 0.30250803
2 c39 d20 2.80 0.2788867 10 0.08819171
3 c39 d21 2.74 0.9834181 10 0.31098410
4 c52 d16 2.26 0.4452215 10 0.14079141
5 c52 d20 3.11 0.7908505 10 0.25008887
6 c52 d21 1.47 0.2110819 10 0.06674995
> ggplot(cabbage_exp, aes(x=Date, y=Weight, fill=Cultivar)) +
geom_bar(position = "dodge")
Error: stat_count() must not be used with a y aesthetic.
# 上述报错是因为，在geom_bar()中没有修改stat，默认为"bin"
# stat为"bin"时，”用于统计x中个元素的数目，不应该指定y
> ggplot(cabbage_exp, aes(x=Date, y=Weight, fill=Cultivar)) +
geom_bar(position = "dodge", stat = "identity")
ggplot(cabbage_exp, aes(x=Date, y=Weight, fill=Cultivar)) +
geom_bar(position = "stack", stat = "identity")
ggplot(cabbage_exp, aes(x=Date, y=Weight, fill=Cultivar)) +
geom_bar(position = "fill", stat = "identity")
#Making a Bar Graph of Counts
ggplot(diamonds, aes(x=cut)) + geom_bar() # geom_bar() 等同于 geom_bar(stat=“bin”)
> #Using colors in a Bar Graph
> str(uspopchange)
'data.frame': 50 obs. of 4 variables:
$ State : chr "Alabama" "Alaska" "Arizona" "Arkansas" ...
$ Abb : chr "AL" "AK" "AZ" "AR" ...
$ Region: Factor w/ 4 levels "Northeast","South",..: 2 4 4 2 4 4 1 2 2 2 ...
$ Change: num 7.5 13.3 24.6 9.1 10 16.9 4.9 14.6 17.6 18.3 ...
> upc <- subset(uspopchange, rank(Change)>40) #表示对change排序后，取第40之后的数据
> upc #第一列为该行在原本数据集uspopchange中的行数
State Abb Region Change
3 Arizona AZ West 24.6
6 Colorado CO West 16.9
10 Florida FL South 17.6
11 Georgia GA South 18.3
13 Idaho ID West 21.1
29 Nevada NV West 35.1
34 North Carolina NC South 18.5
41 South Carolina SC South 15.3
44 Texas TX South 20.6
45 Utah UT West 23.8
> ggplot(upc, aes(x=Abb, y=Change, fill=Region)) + geom_bar(stat = "identity")
ggplot(upc, aes(x=reorder(Abb, Change), y=Change, fill=Region)) +
geom_bar(stat = "identity", color = "black")
#reorder(Abb, Change)排序,前一个填factor,后面填数据，要求factor和数据的长度一致
> #Coloring Negative and Positive Bars Differently
> str(climate)
'data.frame': 499 obs. of 6 variables:
$ Source : chr "Berkeley" "Berkeley" "Berkeley" "Berkeley" ...
$ Year : num 1800 1801 1802 1803 1804 ...
$ Anomaly1y : num NA NA NA NA NA NA NA NA NA NA ...
$ Anomaly5y : num NA NA NA NA NA NA NA NA NA NA ...
$ 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 ...
> csub <- subset(climate, Source=="Berkeley" & Year>=1900)
> csub$pos <- csub$Anomaly10y >= 0 #新增一列“pos”储存Anomaly10y是否大于等于0的返回值（True或False）
> str(csub)
'data.frame': 105 obs. of 7 variables:
$ Source : chr "Berkeley" "Berkeley" "Berkeley" "Berkeley" ...
$ Year : num 1900 1901 1902 1903 1904 ...
$ Anomaly1y : num NA NA NA NA NA NA NA NA NA NA ...
$ Anomaly5y : num NA NA NA NA NA NA NA NA NA NA ...
$ Anomaly10y: num -0.171 -0.162 -0.177 -0.199 -0.223 -0.241 -0.294 -0.312 -0.328 -0.281 ...
$ Unc10y : num 0.108 0.109 0.108 0.104 0.105 0.107 0.106 0.105 0.103 0.101 ...
$ pos : logi FALSE FALSE FALSE FALSE FALSE FALSE ...
> ggplot(csub, aes(x=Year, y=Anomaly10y, fill=pos)) +
geom_bar(stat = "identity", position = "identity") +
scale_fill_manual(values = c("#669933", "#FFCC66"), guide=FALSE)
#values = c("#669933", "#FFCC66")表示替换fill=pos的两种颜色，guide=FALSE为去掉图例
#Adjusting Bar Width and spacing 调整柱的宽度和间距
ggplot(pg_mean, aes(x=group, y=weight)) + geom_bar(stat = "identity")
ggplot(pg_mean, aes(x=group, y=weight)) + geom_bar(stat = "identity", width = 0.5)
# 默认的 width为 0.9
ggplot(pg_mean, aes(x=group, y=weight)) + geom_bar(stat = "identity", width = 1)
# 默认的 width为 0.9
# Grouped data
ggplot(cabbage_exp, aes(x=Date, y=Weight, fill =Cultivar)) +
geom_bar(stat = "identity", width = 0.5, position = "dodge")
ggplot(cabbage_exp, aes(x=Date, y=Weight, fill =Cultivar)) +
geom_bar(stat = "identity", width = 0.5, position = position_dodge(0.7))
ggplot(cabbage_exp, aes(x=Date, y=Weight, fill =Cultivar)) +
geom_bar(stat = "identity", width = 0.5, position = position_dodge(0.5))
ggplot(cabbage_exp, aes(x=Date, y=Weight, fill =Cultivar)) +
geom_bar(stat = "identity", width = 0.5, position = position_dodge(0.2))
> # Adding labels to a Bar Graph
> # below the top
> cabbage_exp
Cultivar Date Weight sd n se
1 c39 d16 3.18 0.9566144 10 0.30250803
2 c39 d20 2.80 0.2788867 10 0.08819171
3 c39 d21 2.74 0.9834181 10 0.31098410
4 c52 d16 2.26 0.4452215 10 0.14079141
5 c52 d20 3.11 0.7908505 10 0.25008887
6 c52 d21 1.47 0.2110819 10 0.06674995
> ggplot(cabbage_exp, aes(x=interaction(Date,Cultivar), y=Weight)) +
geom_bar(stat = "identity") +
geom_text(aes(label = Weight), vjust = 1.5, colour = "white")
> #x=interaction(Date,Cultivar)表示对每一行的Date和Cultivar进行组合
> #aes(label = Weight)表示标注的内容为对应的Weight值
> #vjust>0则label位于顶端下部，colour = "white"表示字体颜色为白色
#Above the top
ggplot(cabbage_exp, aes(x=interaction(Date,Cultivar), y=Weight)) +
geom_bar(stat = "identity") +
geom_text(aes(label = Weight), vjust = -0.2)
#Adjust y limits to be a little higher
ggplot(cabbage_exp, aes(x=interaction(Date,Cultivar), y=Weight)) +
geom_bar(stat = "identity") +
geom_text(aes(label = Weight), vjust = -0.2) +
ylim(0, max(cabbage_exp$Weight)*1.05)
#Adjust y limits to be higher
ggplot(cabbage_exp, aes(x=interaction(Date,Cultivar), y=Weight)) +
geom_bar(stat = "identity") +
geom_text(aes(label = Weight), vjust = -0.2) +
ylim(0, max(cabbage_exp$Weight)*1.5)
# Map y position slightly above bar top
ggplot(cabbage_exp, aes(x=interaction(Date,Cultivar), y=Weight)) +
geom_bar(stat = "identity") +
geom_text(aes(y=Weight+0.1, label = Weight))
ggplot(cabbage_exp, aes(x=interaction(Date,Cultivar), y=Weight)) +
geom_bar(stat = "identity") +
geom_text(aes(y=Weight-0.1, label = Weight))
ggplot(cabbage_exp, aes(x=Date, y=Weight, fill = Cultivar)) +
geom_bar(stat = "identity", position = "dodge") +
geom_text(aes(y=Weight+0.15, label = Weight), position = position_dodge(0.9), size=4)
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