ggplot2 和一行中的第一个数据点
ggplot2 and first data point in a line
我正在使用 ggplot2 创建两个图，然后使用 grid.arrange 将它们合并在一起。我应该说这两个图也都使用 facet_grid 进行视觉调整。
我的问题是底部图实际上是一个数据 table，由于方面。我有办法调整这个吗？我想对此进行调整，这样分数就不会被切断。
这里是重现它的数据：
df <- structure(list(SurveyID = c(16L, 16L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L,
26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L,
26L, 26L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L,
47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L,
56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L,
56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 76L, 76L,
76L, 76L, 76L, 76L, 76L, 76L, 76L, 76L, 76L, 76L, 76L, 76L, 76L,
76L, 76L, 76L, 76L, 76L, 76L, 76L, 76L, 76L, 83L, 83L, 83L, 83L
), MEPSID = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
), ServiceID = structure(c(1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L), .Label = c("Army", "Navy", "Marines", "Air Force"
), class = "factor"), SurveyReturnedYear = c(2012L, 2012L, 2012L,
2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L,
2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L,
2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L,
2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L,
2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L,
2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L,
2013L, 2013L, 2013L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L,
2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L,
2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L,
2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L,
2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L,
2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L), SurveyReturnedMonth = c(10L, 10L,
10L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 5L,
5L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L, 9L,
9L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,
5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L,
9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 12L,
12L, 12L, 12L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L,
4L, 4L, 4L, 4L), CompletedSurvey = c(23L, 19L, 38L, 16L, 11L,
16L, 38L, 19L, 6L, 14L, 41L, 10L, 6L, 32L, 46L, 18L, 12L, 30L,
35L, 18L, 11L, 32L, 23L, 19L, 8L, 24L, 46L, 19L, 18L, 28L, 30L,
19L, 12L, 27L, 32L, 15L, 20L, 31L, 34L, 26L, 30L, 25L, 26L, 17L,
41L, 16L, 24L, 12L, 43L, 23L, 22L, 15L, 29L, 21L, 22L, 18L, 38L,
10L, 20L, 13L, 46L, 19L, 19L, 9L, 32L, 10L, 17L, 27L, 31L, 21L,
17L, 18L, 30L, 18L, 19L, 20L, 22L, 23L, 17L, 17L, 34L, 21L, 16L,
4L, 34L, 29L, 20L, 18L, 25L, 21L, 24L, 19L, 15L, 16L, 18L, 13L,
28L, 19L, 24L, 0L, 23L, 13L, 13L, 2L, 34L, 13L, 22L, 4L, 17L,
26L, 5L, 17L, 27L, 18L, 30L, 0L, 30L, 11L, 34L, 0L, 27L, 9L,
34L, 0L), TotalSurvey = c(41L, 19L, 47L, 22L, 43L, 21L, 49L,
23L, 39L, 16L, 44L, 11L, 49L, 34L, 56L, 33L, 39L, 33L, 42L, 21L,
50L, 37L, 56L, 23L, 34L, 26L, 53L, 19L, 36L, 32L, 44L, 21L, 38L,
27L, 49L, 18L, 41L, 34L, 58L, 26L, 37L, 25L, 40L, 21L, 44L, 17L,
51L, 16L, 51L, 24L, 32L, 22L, 34L, 21L, 37L, 20L, 44L, 10L, 36L,
18L, 59L, 21L, 35L, 13L, 46L, 12L, 44L, 29L, 49L, 21L, 36L, 18L,
47L, 19L, 41L, 21L, 29L, 23L, 40L, 20L, 39L, 21L, 38L, 4L, 41L,
30L, 54L, 21L, 30L, 22L, 56L, 24L, 19L, 16L, 49L, 25L, 34L, 22L,
54L, 20L, 33L, 14L, 40L, 10L, 37L, 14L, 43L, 23L, 27L, 30L, 40L,
22L, 34L, 19L, 37L, 23L, 32L, 19L, 37L, 26L, 35L, 11L, 37L, 31L
), meps_labels = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L), .Label = c("Albany", "Albuquerque", "Amarillo",
"Anchorage", "Atlanta", "Baltimore", "Beckley", "Boise", "Boston",
"Buffalo", "Butte", "Charlotte", "Chicago", "Cleveland", "Columbus",
"Dallas", "Denver", "Des Moines", "Detroit", "El Paso", "Fargo",
"Fort Dix", "Fort Jackson", "Fort Lee", "Harrisburg", "Honolulu",
"Houston", "Indianapolis", "Jackson", "Jacksonville", "Kansas City",
"Knoxville", "Lansing", "Little Rock", "Los Angeles", "Louisville",
"Memphis", "Miami", "Milwaukee", "Minneapolis", "Montgomery",
"Nashville", "New Orleans", "New York", "Oklahoma City", "Omaha",
"Phoenix", "Pittsburgh", "Portland, ME", "Portland, OR", "Raleigh",
"Sacramento", "Salt Lake City", "San Antonio", "San Diego", "San Jose",
"San Juan", "Seattle", "Shreveport", "Sioux Falls", "Spokane",
"Springfield", "St. Louis", "Syracuse", "Tampa"), class = "factor"),
RR = c(56, 100, 81, 73, 26, 76, 78, 83, 15, 88, 93, 91, 12,
94, 82, 55, 31, 91, 83, 86, 22, 86, 41, 83, 24, 92, 87, 100,
50, 88, 68, 90, 32, 100, 65, 83, 49, 91, 59, 100, 81, 100,
65, 81, 93, 94, 47, 75, 84, 96, 69, 68, 85, 100, 59, 90,
86, 100, 56, 72, 78, 90, 54, 69, 70, 83, 39, 93, 63, 100,
47, 100, 64, 95, 46, 95, 76, 100, 42, 85, 87, 100, 42, 100,
83, 97, 37, 86, 83, 95, 43, 79, 79, 100, 37, 52, 82, 86,
44, 0, 70, 93, 32, 20, 92, 93, 51, 17, 63, 87, 12, 77, 79,
95, 81, 0, 94, 58, 92, 0, 77, 82, 92, 0), Time = structure(c(15614,
15614, 15614, 15614, 15645, 15645, 15645, 15645, 15675, 15675,
15675, 15675, 15706, 15706, 15706, 15706, 15737, 15737, 15737,
15737, 15765, 15765, 15765, 15765, 15796, 15796, 15796, 15796,
15826, 15826, 15826, 15826, 15857, 15857, 15857, 15857, 15887,
15887, 15887, 15887, 15918, 15918, 15918, 15918, 15949, 15949,
15949, 15949, 15979, 15979, 15979, 15979, 16010, 16010, 16010,
16010, 16040, 16040, 16040, 16040, 16071, 16071, 16071, 16071,
16102, 16102, 16102, 16102, 16130, 16130, 16130, 16130, 16161,
16161, 16161, 16161, 16191, 16191, 16191, 16191, 16222, 16222,
16222, 16222, 16252, 16252, 16252, 16252, 16283, 16283, 16283,
16283, 16314, 16314, 16314, 16314, 16344, 16344, 16344, 16344,
16375, 16375, 16375, 16375, 16405, 16405, 16405, 16405, 16436,
16436, 16436, 16436, 16467, 16467, 16467, 16467, 16495, 16495,
16495, 16495, 16526, 16526, 16526, 16526), class = "Date"),
Year = c("2012", "2012", "2012", "2012", "2012", "2012",
"2012", "2012", "2012", "2012", "2012", "2012", "2013", "2013",
"2013", "2013", "2013", "2013", "2013", "2013", "2013", "2013",
"2013", "2013", "2013", "2013", "2013", "2013", "2013", "2013",
"2013", "2013", "2013", "2013", "2013", "2013", "2013", "2013",
"2013", "2013", "2013", "2013", "2013", "2013", "2013", "2013",
"2013", "2013", "2013", "2013", "2013", "2013", "2013", "2013",
"2013", "2013", "2013", "2013", "2013", "2013", "2014", "2014",
"2014", "2014", "2014", "2014", "2014", "2014", "2014", "2014",
"2014", "2014", "2014", "2014", "2014", "2014", "2014", "2014",
"2014", "2014", "2014", "2014", "2014", "2014", "2014", "2014",
"2014", "2014", "2014", "2014", "2014", "2014", "2014", "2014",
"2014", "2014", "2014", "2014", "2014", "2014", "2014", "2014",
"2014", "2014", "2014", "2014", "2014", "2014", "2015", "2015",
"2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015",
"2015", "2015", "2015", "2015", "2015", "2015")), .Names = c("SurveyID",
"MEPSID", "ServiceID", "SurveyReturnedYear", "SurveyReturnedMonth",
"CompletedSurvey", "TotalSurvey", "meps_labels", "RR", "Time",
"Year"), row.names = c(1L, 2L, 3L, 4L, 261L, 262L, 263L, 264L,
521L, 522L, 523L, 524L, 781L, 782L, 783L, 784L, 1041L, 1042L,
1043L, 1044L, 1301L, 1302L, 1303L, 1304L, 1561L, 1562L, 1563L,
1564L, 1821L, 1822L, 1823L, 1824L, 2081L, 2082L, 2083L, 2084L,
2341L, 2342L, 2343L, 2344L, 2601L, 2602L, 2603L, 2604L, 2861L,
2862L, 2863L, 2864L, 3121L, 3122L, 3123L, 3124L, 3381L, 3382L,
3383L, 3384L, 3641L, 3642L, 3643L, 3644L, 3901L, 3902L, 3903L,
3904L, 4161L, 4162L, 4163L, 4164L, 4421L, 4422L, 4423L, 4424L,
4681L, 4682L, 4683L, 4684L, 4941L, 4942L, 4943L, 4944L, 5201L,
5202L, 5203L, 5204L, 5461L, 5462L, 5463L, 5464L, 5721L, 5722L,
5723L, 5724L, 5981L, 5982L, 5983L, 5984L, 6241L, 6242L, 6243L,
6244L, 6501L, 6502L, 6503L, 6504L, 6761L, 6762L, 6763L, 6764L,
7021L, 7022L, 7023L, 7024L, 7281L, 7282L, 7283L, 7284L, 7541L,
7542L, 7543L, 7544L, 7801L, 7802L, 7803L, 7804L), class = "data.frame")
代码：
library(ggplot2)
library(grid)
library(scales)
library(gridExtra)
p<- ggplot(data=df[df$MEPSID==1,],
aes(x=Time, y=RR, colour=ServiceID, group=ServiceID, label=round(RR)))+
scale_y_continuous(breaks=seq(0, 100, 10))+
labs(y="Response Rate")+
coord_cartesian(ylim=c(0, 110))+
geom_line(size=.5)+
geom_point()+
scale_color_manual(values=c("green4","blue4","red4","dodgerblue"))+
ggtitle("Counts")+
theme(plot.title=element_text(size=18, face="bold", vjust=1),
axis.title=element_text(size=16),
axis.text.x=element_text(size=10, angle=90),
axis.line=element_line(colour="black", size=.2),
legend.background = element_rect(fill="transparent"),
legend.position="top",
legend.title=element_blank(),
legend.margin=unit(-0.6, "cm"),
legend.position="none",
legend.text=element_text(size=14),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.y = element_blank(),
panel.background = element_blank(),
panel.grid.major.y=element_line(colour="gray", linetype="solid", size=.2))+ # or theme_blank())
scale_x_date(labels = date_format("%b"), breaks=date_breaks("month"))+
facet_grid(~Year, scales="free", space="free")
p2<-ggplot(df[df$MEPSID==1,], aes(x = Time, y = ServiceID, label=format(round(RR), nsmall=0), colour = ServiceID)) +
geom_text(size = 3.5) +
theme(
panel.grid.major = element_blank(),
legend.position = "none",
panel.border = element_blank(),
panel.background = element_blank(),
axis.text.x = element_text(),
axis.ticks = element_blank(),
plot.margin = unit(c(-0.5,1, 0, 0.5), "lines")) +
xlab(NULL) +
ylab(NULL)+
scale_x_date(labels=c(), breaks=date_breaks("month"), expand=c(0.05,0.05))+
facet_grid(~Year, scales="free", space="free_x")+
scale_y_discrete(limits=rev(levels(df$ServiceID)))+
scale_color_manual(values=c("green4","blue4","red4","dodgerblue"))
grid.arrange(arrangeGrob(p,p2,
nrow=2, heights=c(5,1)))
您可以使用 geom_blank 微调多面刻度。
grid.arrange(p + geom_blank(data = data.frame(Time = as.Date(c("2012-09-20", "2012-12-15",
"2014-12-20", "2015-04-10")),
RR = 1:4,
Year = c(2012, 2012, 2015, 2015)),
aes(colour = NULL, group = NULL, label = NULL)) ,
p2 + geom_blank(data = data.frame(Time = as.Date(c("2012-09-20", "2012-12-15",
"2014-12-20", "2015-04-10")),
ServiceID = 1:4,
Year = c(2012, 2012, 2015, 2015)),
aes(colour = NULL, group = NULL, label = NULL)) ,
nrow=2, heights=c(5,1))
另一种选择是使用 hjust 参数作为 aes 来调整文本。但首先你应该将它作为自己的列添加到数据中，你将传递给 ggplot 命令：
library(data.table)
DX <- setDT(df[df$MEPSID==1,])
DX[,hjust:=ifelse(Time==min(Time),0.1,ifelse(Time==max(Time),0.8,0.4)),Year] #This creates a new variable called hjust
p2<-ggplot(DX,
aes(x = Time, y = ServiceID, label=format(round(RR), nsmall=0),
colour = ServiceID,hjust=hjust)) +
## the rest of the plot 2
添加一些解释：
此处您将使用（时间与服务 ID）按年份绘制文本。
因为我们想水平移动我们的文本，我们将根据时间（x 坐标）的值来做。更准确地说，只会将左边的点移到右边，将右边的点移到左边。这将通过为每组值（左与右）设置不同的 hjust 值来完成。
所以对于每一年（每个方面），我将水平调整对应于时间的最小点（方面的最左边的点）和时间的最大值（方面的最右边的点）的点.其他点我这里也不需要调整了
DX[,hjust:=ifelse(Time==min(Time),0.1, ## extreme left point
ifelse(Time==max(Time),0.8, ## extreme right points
0.4)), ## others
Year] ## for each facet
您可以使用 ave:
在 base R 中执行 trsnformation
ave(as.numeric(xx$Time),xx$Year,
FUN=function(x)
ifelse(x==min(x),0.1,ifelse(x==max(x),0.8,0.4)))
我正在使用 ggplot2 创建两个图，然后使用 grid.arrange 将它们合并在一起。我应该说这两个图也都使用 facet_grid 进行视觉调整。
我的问题是底部图实际上是一个数据 table，由于方面。我有办法调整这个吗？我想对此进行调整，这样分数就不会被切断。
这里是重现它的数据：
df <- structure(list(SurveyID = c(16L, 16L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L,
26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L, 26L,
26L, 26L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L,
47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L, 47L,
56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L,
56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 56L, 76L, 76L,
76L, 76L, 76L, 76L, 76L, 76L, 76L, 76L, 76L, 76L, 76L, 76L, 76L,
76L, 76L, 76L, 76L, 76L, 76L, 76L, 76L, 76L, 83L, 83L, 83L, 83L
), MEPSID = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L
), ServiceID = structure(c(1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L, 1L,
2L, 3L, 4L), .Label = c("Army", "Navy", "Marines", "Air Force"
), class = "factor"), SurveyReturnedYear = c(2012L, 2012L, 2012L,
2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L, 2012L,
2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L,
2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L,
2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L,
2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L,
2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L, 2013L,
2013L, 2013L, 2013L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L,
2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L,
2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L,
2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L,
2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2014L,
2014L, 2014L, 2014L, 2014L, 2014L, 2014L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L, 2015L,
2015L, 2015L, 2015L, 2015L), SurveyReturnedMonth = c(10L, 10L,
10L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 5L,
5L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 9L, 9L, 9L,
9L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 12L, 12L, 12L, 12L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L,
5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L,
9L, 9L, 9L, 9L, 10L, 10L, 10L, 10L, 11L, 11L, 11L, 11L, 12L,
12L, 12L, 12L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L,
4L, 4L, 4L, 4L), CompletedSurvey = c(23L, 19L, 38L, 16L, 11L,
16L, 38L, 19L, 6L, 14L, 41L, 10L, 6L, 32L, 46L, 18L, 12L, 30L,
35L, 18L, 11L, 32L, 23L, 19L, 8L, 24L, 46L, 19L, 18L, 28L, 30L,
19L, 12L, 27L, 32L, 15L, 20L, 31L, 34L, 26L, 30L, 25L, 26L, 17L,
41L, 16L, 24L, 12L, 43L, 23L, 22L, 15L, 29L, 21L, 22L, 18L, 38L,
10L, 20L, 13L, 46L, 19L, 19L, 9L, 32L, 10L, 17L, 27L, 31L, 21L,
17L, 18L, 30L, 18L, 19L, 20L, 22L, 23L, 17L, 17L, 34L, 21L, 16L,
4L, 34L, 29L, 20L, 18L, 25L, 21L, 24L, 19L, 15L, 16L, 18L, 13L,
28L, 19L, 24L, 0L, 23L, 13L, 13L, 2L, 34L, 13L, 22L, 4L, 17L,
26L, 5L, 17L, 27L, 18L, 30L, 0L, 30L, 11L, 34L, 0L, 27L, 9L,
34L, 0L), TotalSurvey = c(41L, 19L, 47L, 22L, 43L, 21L, 49L,
23L, 39L, 16L, 44L, 11L, 49L, 34L, 56L, 33L, 39L, 33L, 42L, 21L,
50L, 37L, 56L, 23L, 34L, 26L, 53L, 19L, 36L, 32L, 44L, 21L, 38L,
27L, 49L, 18L, 41L, 34L, 58L, 26L, 37L, 25L, 40L, 21L, 44L, 17L,
51L, 16L, 51L, 24L, 32L, 22L, 34L, 21L, 37L, 20L, 44L, 10L, 36L,
18L, 59L, 21L, 35L, 13L, 46L, 12L, 44L, 29L, 49L, 21L, 36L, 18L,
47L, 19L, 41L, 21L, 29L, 23L, 40L, 20L, 39L, 21L, 38L, 4L, 41L,
30L, 54L, 21L, 30L, 22L, 56L, 24L, 19L, 16L, 49L, 25L, 34L, 22L,
54L, 20L, 33L, 14L, 40L, 10L, 37L, 14L, 43L, 23L, 27L, 30L, 40L,
22L, 34L, 19L, 37L, 23L, 32L, 19L, 37L, 26L, 35L, 11L, 37L, 31L
), meps_labels = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L), .Label = c("Albany", "Albuquerque", "Amarillo",
"Anchorage", "Atlanta", "Baltimore", "Beckley", "Boise", "Boston",
"Buffalo", "Butte", "Charlotte", "Chicago", "Cleveland", "Columbus",
"Dallas", "Denver", "Des Moines", "Detroit", "El Paso", "Fargo",
"Fort Dix", "Fort Jackson", "Fort Lee", "Harrisburg", "Honolulu",
"Houston", "Indianapolis", "Jackson", "Jacksonville", "Kansas City",
"Knoxville", "Lansing", "Little Rock", "Los Angeles", "Louisville",
"Memphis", "Miami", "Milwaukee", "Minneapolis", "Montgomery",
"Nashville", "New Orleans", "New York", "Oklahoma City", "Omaha",
"Phoenix", "Pittsburgh", "Portland, ME", "Portland, OR", "Raleigh",
"Sacramento", "Salt Lake City", "San Antonio", "San Diego", "San Jose",
"San Juan", "Seattle", "Shreveport", "Sioux Falls", "Spokane",
"Springfield", "St. Louis", "Syracuse", "Tampa"), class = "factor"),
RR = c(56, 100, 81, 73, 26, 76, 78, 83, 15, 88, 93, 91, 12,
94, 82, 55, 31, 91, 83, 86, 22, 86, 41, 83, 24, 92, 87, 100,
50, 88, 68, 90, 32, 100, 65, 83, 49, 91, 59, 100, 81, 100,
65, 81, 93, 94, 47, 75, 84, 96, 69, 68, 85, 100, 59, 90,
86, 100, 56, 72, 78, 90, 54, 69, 70, 83, 39, 93, 63, 100,
47, 100, 64, 95, 46, 95, 76, 100, 42, 85, 87, 100, 42, 100,
83, 97, 37, 86, 83, 95, 43, 79, 79, 100, 37, 52, 82, 86,
44, 0, 70, 93, 32, 20, 92, 93, 51, 17, 63, 87, 12, 77, 79,
95, 81, 0, 94, 58, 92, 0, 77, 82, 92, 0), Time = structure(c(15614,
15614, 15614, 15614, 15645, 15645, 15645, 15645, 15675, 15675,
15675, 15675, 15706, 15706, 15706, 15706, 15737, 15737, 15737,
15737, 15765, 15765, 15765, 15765, 15796, 15796, 15796, 15796,
15826, 15826, 15826, 15826, 15857, 15857, 15857, 15857, 15887,
15887, 15887, 15887, 15918, 15918, 15918, 15918, 15949, 15949,
15949, 15949, 15979, 15979, 15979, 15979, 16010, 16010, 16010,
16010, 16040, 16040, 16040, 16040, 16071, 16071, 16071, 16071,
16102, 16102, 16102, 16102, 16130, 16130, 16130, 16130, 16161,
16161, 16161, 16161, 16191, 16191, 16191, 16191, 16222, 16222,
16222, 16222, 16252, 16252, 16252, 16252, 16283, 16283, 16283,
16283, 16314, 16314, 16314, 16314, 16344, 16344, 16344, 16344,
16375, 16375, 16375, 16375, 16405, 16405, 16405, 16405, 16436,
16436, 16436, 16436, 16467, 16467, 16467, 16467, 16495, 16495,
16495, 16495, 16526, 16526, 16526, 16526), class = "Date"),
Year = c("2012", "2012", "2012", "2012", "2012", "2012",
"2012", "2012", "2012", "2012", "2012", "2012", "2013", "2013",
"2013", "2013", "2013", "2013", "2013", "2013", "2013", "2013",
"2013", "2013", "2013", "2013", "2013", "2013", "2013", "2013",
"2013", "2013", "2013", "2013", "2013", "2013", "2013", "2013",
"2013", "2013", "2013", "2013", "2013", "2013", "2013", "2013",
"2013", "2013", "2013", "2013", "2013", "2013", "2013", "2013",
"2013", "2013", "2013", "2013", "2013", "2013", "2014", "2014",
"2014", "2014", "2014", "2014", "2014", "2014", "2014", "2014",
"2014", "2014", "2014", "2014", "2014", "2014", "2014", "2014",
"2014", "2014", "2014", "2014", "2014", "2014", "2014", "2014",
"2014", "2014", "2014", "2014", "2014", "2014", "2014", "2014",
"2014", "2014", "2014", "2014", "2014", "2014", "2014", "2014",
"2014", "2014", "2014", "2014", "2014", "2014", "2015", "2015",
"2015", "2015", "2015", "2015", "2015", "2015", "2015", "2015",
"2015", "2015", "2015", "2015", "2015", "2015")), .Names = c("SurveyID",
"MEPSID", "ServiceID", "SurveyReturnedYear", "SurveyReturnedMonth",
"CompletedSurvey", "TotalSurvey", "meps_labels", "RR", "Time",
"Year"), row.names = c(1L, 2L, 3L, 4L, 261L, 262L, 263L, 264L,
521L, 522L, 523L, 524L, 781L, 782L, 783L, 784L, 1041L, 1042L,
1043L, 1044L, 1301L, 1302L, 1303L, 1304L, 1561L, 1562L, 1563L,
1564L, 1821L, 1822L, 1823L, 1824L, 2081L, 2082L, 2083L, 2084L,
2341L, 2342L, 2343L, 2344L, 2601L, 2602L, 2603L, 2604L, 2861L,
2862L, 2863L, 2864L, 3121L, 3122L, 3123L, 3124L, 3381L, 3382L,
3383L, 3384L, 3641L, 3642L, 3643L, 3644L, 3901L, 3902L, 3903L,
3904L, 4161L, 4162L, 4163L, 4164L, 4421L, 4422L, 4423L, 4424L,
4681L, 4682L, 4683L, 4684L, 4941L, 4942L, 4943L, 4944L, 5201L,
5202L, 5203L, 5204L, 5461L, 5462L, 5463L, 5464L, 5721L, 5722L,
5723L, 5724L, 5981L, 5982L, 5983L, 5984L, 6241L, 6242L, 6243L,
6244L, 6501L, 6502L, 6503L, 6504L, 6761L, 6762L, 6763L, 6764L,
7021L, 7022L, 7023L, 7024L, 7281L, 7282L, 7283L, 7284L, 7541L,
7542L, 7543L, 7544L, 7801L, 7802L, 7803L, 7804L), class = "data.frame")
代码：
library(ggplot2)
library(grid)
library(scales)
library(gridExtra)
p<- ggplot(data=df[df$MEPSID==1,],
aes(x=Time, y=RR, colour=ServiceID, group=ServiceID, label=round(RR)))+
scale_y_continuous(breaks=seq(0, 100, 10))+
labs(y="Response Rate")+
coord_cartesian(ylim=c(0, 110))+
geom_line(size=.5)+
geom_point()+
scale_color_manual(values=c("green4","blue4","red4","dodgerblue"))+
ggtitle("Counts")+
theme(plot.title=element_text(size=18, face="bold", vjust=1),
axis.title=element_text(size=16),
axis.text.x=element_text(size=10, angle=90),
axis.line=element_line(colour="black", size=.2),
legend.background = element_rect(fill="transparent"),
legend.position="top",
legend.title=element_blank(),
legend.margin=unit(-0.6, "cm"),
legend.position="none",
legend.text=element_text(size=14),
panel.grid.minor.x = element_blank(),
panel.grid.major.x = element_blank(),
panel.grid.minor.y = element_blank(),
panel.background = element_blank(),
panel.grid.major.y=element_line(colour="gray", linetype="solid", size=.2))+ # or theme_blank())
scale_x_date(labels = date_format("%b"), breaks=date_breaks("month"))+
facet_grid(~Year, scales="free", space="free")
p2<-ggplot(df[df$MEPSID==1,], aes(x = Time, y = ServiceID, label=format(round(RR), nsmall=0), colour = ServiceID)) +
geom_text(size = 3.5) +
theme(
panel.grid.major = element_blank(),
legend.position = "none",
panel.border = element_blank(),
panel.background = element_blank(),
axis.text.x = element_text(),
axis.ticks = element_blank(),
plot.margin = unit(c(-0.5,1, 0, 0.5), "lines")) +
xlab(NULL) +
ylab(NULL)+
scale_x_date(labels=c(), breaks=date_breaks("month"), expand=c(0.05,0.05))+
facet_grid(~Year, scales="free", space="free_x")+
scale_y_discrete(limits=rev(levels(df$ServiceID)))+
scale_color_manual(values=c("green4","blue4","red4","dodgerblue"))
grid.arrange(arrangeGrob(p,p2,
nrow=2, heights=c(5,1)))
您可以使用 geom_blank 微调多面刻度。
grid.arrange(p + geom_blank(data = data.frame(Time = as.Date(c("2012-09-20", "2012-12-15",
"2014-12-20", "2015-04-10")),
RR = 1:4,
Year = c(2012, 2012, 2015, 2015)),
aes(colour = NULL, group = NULL, label = NULL)) ,
p2 + geom_blank(data = data.frame(Time = as.Date(c("2012-09-20", "2012-12-15",
"2014-12-20", "2015-04-10")),
ServiceID = 1:4,
Year = c(2012, 2012, 2015, 2015)),
aes(colour = NULL, group = NULL, label = NULL)) ,
nrow=2, heights=c(5,1))
另一种选择是使用 hjust 参数作为 aes 来调整文本。但首先你应该将它作为自己的列添加到数据中，你将传递给 ggplot 命令：
library(data.table)
DX <- setDT(df[df$MEPSID==1,])
DX[,hjust:=ifelse(Time==min(Time),0.1,ifelse(Time==max(Time),0.8,0.4)),Year] #This creates a new variable called hjust
p2<-ggplot(DX,
aes(x = Time, y = ServiceID, label=format(round(RR), nsmall=0),
colour = ServiceID,hjust=hjust)) +
## the rest of the plot 2
添加一些解释：
此处您将使用（时间与服务 ID）按年份绘制文本。 因为我们想水平移动我们的文本，我们将根据时间（x 坐标）的值来做。更准确地说，只会将左边的点移到右边，将右边的点移到左边。这将通过为每组值（左与右）设置不同的 hjust 值来完成。
所以对于每一年（每个方面），我将水平调整对应于时间的最小点（方面的最左边的点）和时间的最大值（方面的最右边的点）的点.其他点我这里也不需要调整了
DX[,hjust:=ifelse(Time==min(Time),0.1, ## extreme left point
ifelse(Time==max(Time),0.8, ## extreme right points
0.4)), ## others
Year] ## for each facet
您可以使用 ave:
ave(as.numeric(xx$Time),xx$Year,
FUN=function(x)
ifelse(x==min(x),0.1,ifelse(x==max(x),0.8,0.4)))