如何在ggplot中添加图例（不显示） [英] How to add a legend in ggplot (not showing up)
本文介绍了如何在ggplot中添加图例（不显示）的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我想添加一个图例，其中红线=拒绝率，深蓝色=平均值（reject_rate）
，浅蓝色=平均值+2标准差
我已将线条绘制得很好，但似乎无法显示图例。非常感谢
>
数据
> dput（sub）
structure（list（Report_Date = structure（c（16311,16318,16325，$ b $ 16332,16339,16346,16353,166360,16367,16374,16381,16388，
16311,16318,16325,16332,16339,16346,16360,16367,16374，
16381,16388,16311,16318,16325,16332,16339,16346,16353，$ b $ 16360,16367,16374， 16381，16388，16311，16318，16325，16332，
16339，16346，16360，16367，16374，16388，16311，16318，16325，
16332，16339，16346，16353，16360，16367， 16374,16381,16388，
16311,16318,16325,16332,16339,16346,16353,16360,16367，
16374,16381,16388,16311,16318,16325,16332,16339,16346,16344,16384,16384,16384,16384,16384,16384，
16353,166360,16367,16374,16381,16388），class =Date），Regional_Office = structure（c（1L，
1L，1L，1L，1L，1L，1L，1L， 1L，1L，1L，1L，2L，2L，2L，2L，2L，
2L，2L，2L，2L，2L，2L，3L，3L，3L，3L，3L，3L，3L，3L， 3L，3L，
3L，3L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，5L，5L，5L，5L，
5L，5L， 5L，5L，5L，5L，5L，6L，6L，6L，6L，6L，6L， 6L，6L，6L，6L，6L，7L，7L，7L，7L，7L，7L，7L，7L，7L，7L，7L，7L，7L
），。标签= c EARO， EASO， LACRO， MEERO， SAPO， SARO，
的WARO），类= 因子），已批准= C（0.973856209150327，0.917159763313609，
0.913978494623656,0.930612244897959,0.902857142857143,0.952380952380952
1,0.979763912310287 0.950873362445415 0.802325581395349 0.950354609929078
1,0.976284584980237 0.99625 1,0.962962962962963 0.958837772397094 0.958837772397094
1,1,1， 1，0.978723404255319,1,0.993650793650794,0.994897959183674，
1，0.995316159250585,0.966911764705882,1,1,0.991836734693878，
0.995180722891566,0.999535714285714,0.9989010989010989,1.1，
1,1,1， 0.897435897435897，1，0.985507246376812，0.907692307692308，
0.952380952380952，1，0.982558139534884，0.989247311827957，1，
0.985383678440926，0.972555746140652，0.978571428571429，1，0.973352033660589，
0.934504792332268，0.973421926910299，0.985074626865672，1，0.9562043 79562044，
0.901060070671378,0.9981196581196581,0.96875,0.897560975609756，
0.988505747126437,1,0.95,0.895384615384615,0.916666666666667，
0.967741935483871,0.935483870967742,1,1,1,0.948275862068966，
0.994845360824742，1，0.970833333333333，1，0.936781609195402，
0.987854251012146，0.982758620689655），approval_rate = C（97.3856209150327，
91.7159763313609，91.3978494623656，93.0612244897959，90.2857142857143，
95.2380952380952，100，97.9763912310287，95.0873362445415，80.2325581395349
95.0354609929078,100,97.6284584980237,99.625,100,96.2962962962963
95.8837772397094,100,100,100,100,97.8723404255319,100
99.3650793650794 99.4897959183673,100 99.5316159250585 96.6911764705882
100,100，99.1836734693878,99.5180722891566,99.5535714285714
98.9010989010989,100,100,100,100,100,79.7435897435898
100 98.5507246376812 90.7692307692308 95.2380952380952 100
98.2558139534884 ，9 8.9247311827957，100，98.5383678440926，97.2555746140652，
97.8571428571428，100，97.3352033660589，93.4504792332268，97.3421926910299，
98.5074626865672，100，95.6204379562044，90.1060070671378，98.1196581196581，
96.875，89.7560975609756，98.8505747126437，100，95， 89.5384615384615，
91.6666666666667,96.7741935483871,93.5483870967742,100,100，
100,100,94.8275862068966,999.4845360824742,100,97.0833333333333，
100,93.6781609195402,98.7854251012146,98.2758620689655），reject_rate = c（2.61437908496732 ，
8.28402366863905 8.60215053763441 6.93877551020409 9.71428571428572
4.76190476190477,0.22360876897133 4.91266375545851 19.7674418604651
4.96453900709219,0.237154150197628 0.375000000000003,0
3.70370370370371 4.11622276029056 0 ，0,0,0,2,12765957446809，
0，0.634920634920633,0.510204081632648,0,0.468384074941453，
3.30882352941176,0,0,0.816326530612244,0.481927710843377，
0.44642857142 857,1.09890109890109,0,0,0,0,0,10.2564102564103，
0,1.44927536231884,9.23076923076923,4.76190476190477,0.1.74418604651163，
1.0752688172043,0,1.46163215590743,2.74442538593482,2.14285714285715，
0,2.66479663394109,6.54952076677317,2.65780730897009,1.49253731343284，
0,4.37956204379562,9.89399293286219,1.88034188034188,3.125，
10.2439024390244,1.14942528735632,0.5,10.4615384615385,8.33333333333334，
3.2258064516129,6.45161290322581,0， 0，0，0，5.17241379310345，
0.515463917525771,0,2.91666666666667,0,6.32183908045977，
1.21457489878543,1.72413793103449）），.Names = c（Report_Date，
Regional_Office， （5L，6L，7L，8L，9L，10L，11L，12L，13L，14L，
15L，16L， 21L，22L，23L，24L，25L，26L，27L，28L，29L，30L，31L，
36L，37L，38L，39L，40L，41L，42L，43L，44L，45L，46L，47L， 51L，
52L，53L，54L，55L，56L，57L，58L，59L，60L，65L，66L， 67L，68L，
69L，70L，71L，72L，73L，74L，75L，76L，81L，82L，83L，84L，85L，$ b $ 86L，87L，88L，89L，90L，91L， 92L，97L，98L，99L，100L，101L，
102L，103L，104L，105L，106L，107L，108L），class =data.frame）
代码
regional_trend< - 功能（子，n_weeks，COLS）{
ggplot（子，AES（REPORT_DATE，reject_rate））+
geom_point（颜色= 红）+
facet_wrap（〜Regional_Office ，ncol = cols）+
geom_line（color =red，size = 1.5）+
geom_text（aes（y = reject_rate，label = round（reject_rate，1）），vjust = -1， （c（min，sub $ Report_Date），max（sub $ Report_Date）））+
ylim（c（0，max（sub $ reject_rate，size = 4.5，color =red）+
xlim +）+
ggtitle（粘贴（按区域拒绝率\ n（滚动，n周，周）））+
主题（plot.title = element_text（size = 15） ，color =bold，vjust = 2），
axis.title.x = element_text（color =grey20，size = 14，
angle = 0，hjust = .5，vjust = 0，face =plain），
axis.title。 y = element_text（color =grey20，size = 14，
angle = 90，hjust = .5，vjust = 1，face =plain）
）+
xlab ）+
ylab（拒绝率（％））+
geom_hline（yintercept =平均值（sub $ reject_rate），线型=虚线，颜色=蓝色，尺寸= .7）+
geom_hline（yintercept = mean（sub $ reject_rate）+（sd（sub $ reject_rate）* 2），
linetype =longdash，color =lightblue3，size =。 7）
}
regional_trend（reg_last_12wks，12,1）
解决方案
通常情况下，您应该在美学调用中使用颜色，以便自动工作。你也可以用黑客来实现它：在你的情节中添加一个额外的 geom_line 。这通常不是一个好主意，但它应该起作用。
p + geom_line（data = data.frame（x = as.Date（2014-08-29），y = -Inf，
col = c（'拒绝率'，'平均拒绝率'，'平均值+2sd'）），
aes（x，y，color = col））+
scale_color_manual（''，
limits = c（'拒绝率'，'平均拒绝率'，'mean + 2sd'），
values = c（'red'，'blue'，'lightblue3 '））
I'd like to add a legend where the red line = reject rate, dark blue = mean(reject_rate) and light blue = mean + 2 standard deviations
I've got the lines plotted fine, but can't seem to get a legend to show up. Many thanks
data
> dput(sub)
structure(list(Report_Date = structure(c(16311, 16318, 16325,
16332, 16339, 16346, 16353, 16360, 16367, 16374, 16381, 16388,
16311, 16318, 16325, 16332, 16339, 16346, 16360, 16367, 16374,
16381, 16388, 16311, 16318, 16325, 16332, 16339, 16346, 16353,
16360, 16367, 16374, 16381, 16388, 16311, 16318, 16325, 16332,
16339, 16346, 16360, 16367, 16374, 16388, 16311, 16318, 16325,
16332, 16339, 16346, 16353, 16360, 16367, 16374, 16381, 16388,
16311, 16318, 16325, 16332, 16339, 16346, 16353, 16360, 16367,
16374, 16381, 16388, 16311, 16318, 16325, 16332, 16339, 16346,
16353, 16360, 16367, 16374, 16381, 16388), class = "Date"), Regional_Office = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L
), .Label = c("EARO", "EASO", "LACRO", "MEERO", "SAPO", "SARO",
"WARO"), class = "factor"), Approved = c(0.973856209150327, 0.917159763313609,
0.913978494623656, 0.930612244897959, 0.902857142857143, 0.952380952380952,
1, 0.979763912310287, 0.950873362445415, 0.802325581395349, 0.950354609929078,
1, 0.976284584980237, 0.99625, 1, 0.962962962962963, 0.958837772397094,
1, 1, 1, 1, 0.978723404255319, 1, 0.993650793650794, 0.994897959183674,
1, 0.995316159250585, 0.966911764705882, 1, 1, 0.991836734693878,
0.995180722891566, 0.995535714285714, 0.989010989010989, 1, 1,
1, 1, 1, 0.897435897435897, 1, 0.985507246376812, 0.907692307692308,
0.952380952380952, 1, 0.982558139534884, 0.989247311827957, 1,
0.985383678440926, 0.972555746140652, 0.978571428571429, 1, 0.973352033660589,
0.934504792332268, 0.973421926910299, 0.985074626865672, 1, 0.956204379562044,
0.901060070671378, 0.981196581196581, 0.96875, 0.897560975609756,
0.988505747126437, 1, 0.95, 0.895384615384615, 0.916666666666667,
0.967741935483871, 0.935483870967742, 1, 1, 1, 1, 0.948275862068966,
0.994845360824742, 1, 0.970833333333333, 1, 0.936781609195402,
0.987854251012146, 0.982758620689655), approval_rate = c(97.3856209150327,
91.7159763313609, 91.3978494623656, 93.0612244897959, 90.2857142857143,
95.2380952380952, 100, 97.9763912310287, 95.0873362445415, 80.2325581395349,
95.0354609929078, 100, 97.6284584980237, 99.625, 100, 96.2962962962963,
95.8837772397094, 100, 100, 100, 100, 97.8723404255319, 100,
99.3650793650794, 99.4897959183673, 100, 99.5316159250585, 96.6911764705882,
100, 100, 99.1836734693878, 99.5180722891566, 99.5535714285714,
98.9010989010989, 100, 100, 100, 100, 100, 89.7435897435898,
100, 98.5507246376812, 90.7692307692308, 95.2380952380952, 100,
98.2558139534884, 98.9247311827957, 100, 98.5383678440926, 97.2555746140652,
97.8571428571428, 100, 97.3352033660589, 93.4504792332268, 97.3421926910299,
98.5074626865672, 100, 95.6204379562044, 90.1060070671378, 98.1196581196581,
96.875, 89.7560975609756, 98.8505747126437, 100, 95, 89.5384615384615,
91.6666666666667, 96.7741935483871, 93.5483870967742, 100, 100,
100, 100, 94.8275862068966, 99.4845360824742, 100, 97.0833333333333,
100, 93.6781609195402, 98.7854251012146, 98.2758620689655), reject_rate = c(2.61437908496732,
8.28402366863905, 8.60215053763441, 6.93877551020409, 9.71428571428572,
4.76190476190477, 0, 2.02360876897133, 4.91266375545851, 19.7674418604651,
4.96453900709219, 0, 2.37154150197628, 0.375000000000003, 0,
3.70370370370371, 4.11622276029056, 0, 0, 0, 0, 2.12765957446809,
0, 0.634920634920633, 0.510204081632648, 0, 0.468384074941453,
3.30882352941176, 0, 0, 0.816326530612244, 0.481927710843377,
0.44642857142857, 1.09890109890109, 0, 0, 0, 0, 0, 10.2564102564103,
0, 1.44927536231884, 9.23076923076923, 4.76190476190477, 0, 1.74418604651163,
1.0752688172043, 0, 1.46163215590743, 2.74442538593482, 2.14285714285715,
0, 2.66479663394109, 6.54952076677317, 2.65780730897009, 1.49253731343284,
0, 4.37956204379562, 9.89399293286219, 1.88034188034188, 3.125,
10.2439024390244, 1.14942528735632, 0, 5, 10.4615384615385, 8.33333333333334,
3.2258064516129, 6.45161290322581, 0, 0, 0, 0, 5.17241379310345,
0.515463917525771, 0, 2.91666666666667, 0, 6.32183908045977,
1.21457489878543, 1.72413793103449)), .Names = c("Report_Date",
"Regional_Office", "Approved", "approval_rate", "reject_rate"
), row.names = c(5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L,
15L, 16L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L,
36L, 37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 51L,
52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 65L, 66L, 67L, 68L,
69L, 70L, 71L, 72L, 73L, 74L, 75L, 76L, 81L, 82L, 83L, 84L, 85L,
86L, 87L, 88L, 89L, 90L, 91L, 92L, 97L, 98L, 99L, 100L, 101L,
102L, 103L, 104L, 105L, 106L, 107L, 108L), class = "data.frame")
code
regional_trend <- function(sub,n_weeks,cols) {
ggplot(sub, aes(Report_Date, reject_rate))+
geom_point(color="red") +
facet_wrap(~Regional_Office, ncol=cols) +
geom_line(color="red", size=1.5) +
geom_text(aes(y=reject_rate, label=round(reject_rate,1)), vjust=-1, size=4.5,colour="red") +
xlim(c(min(sub$Report_Date),max(sub$Report_Date))) +
ylim(c(0,max(sub$reject_rate+15)))+
ggtitle(paste("Reject Rates by Region \n(Rolling",n_weeks, "weeks)")) +
theme(plot.title = element_text(size=15, face="bold", vjust=2),
axis.text.x = element_text(colour="grey20",size=10,,hjust=.5,vjust=.5),
axis.title.x = element_text(colour="grey20", size=14,
angle=0,hjust=.5, vjust=0, face="plain"),
axis.title.y = element_text(colour="grey20", size=14,
angle=90, hjust=.5, vjust=1,face="plain")
)+
xlab("Week of Receipt") +
ylab("Reject Rate (in %)") +
geom_hline(yintercept=mean(sub$reject_rate), linetype="dashed",colour="blue",size=.7) +
geom_hline(yintercept=mean(sub$reject_rate)+ (sd(sub$reject_rate)*2),
linetype="longdash", colour="lightblue3", size=.7)
}
regional_trend(reg_last_12wks,12,1)
解决方案
Usually, you should have the color within the aesthetics call, for this to work automatically. You can also achieve it with a hack: adding an additional geom_line to your plot. This is normally not a good idea, but it should work.
p + geom_line(data=data.frame(x = as.Date("2014-08-29"), y = -Inf,
col=c('rejection rate', 'mean rejection rate', 'mean + 2sd')),
aes(x, y, color=col)) +
scale_color_manual('',
limits = c('rejection rate', 'mean rejection rate', 'mean + 2sd'),
values = c('red', 'blue', 'lightblue3'))
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