R 带有ggplot2的双比例绘图：为添加的变量添加图例条目
我有两个这样的数据帧：R 带有ggplot2的双比例绘图：为添加的变量添加图例条目,r,ggplot2,R,Ggplot2,我有两个这样的数据帧： dput(plot_1) plot_1<- structure(list(t_exp = c(479.18330748, 550.09264769, 581.27775562, 602.90277249, 729.74280191, 963.299432, 1186.40357135, 1377.06205603, 1604.97385043,
dput(plot_1)
plot_1<- structure(list(t_exp = c(479.18330748, 550.09264769, 581.27775562,
602.90277249, 729.74280191, 963.299432, 1186.40357135, 1377.06205603,
1604.97385043, 1977.32706598, 1528.89847687, 2017.83048618, 2558.91142867,
2422.08428098, 2418.86951627, 2248.93633177, 1908.92844943, 479.18330748,
550.09264769, 581.27775562, 602.90277249, 729.74280191, 963.299432,
1186.40357135, 1377.06205603, 1604.97385043, 1977.32706598, 1528.89847687,
2017.83048618, 2558.91142867, 2422.08428098, 2418.86951627, 2248.93633177,
1908.92844943, 479.18330748, 550.09264769, 581.27775562, 602.90277249,
729.74280191, 963.299432, 1186.40357135, 1377.06205603, 1604.97385043,
1977.32706598, 1528.89847687, 2017.83048618, 2558.91142867, 2422.08428098,
2418.86951627, 2248.93633177, 1908.92844943, 479.18330748, 550.09264769,
581.27775562, 602.90277249, 729.74280191, 963.299432, 1186.40357135,
1377.06205603, 1604.97385043, 1977.32706598, 1528.89847687, 2017.83048618,
2558.91142867, 2422.08428098, 2418.86951627, 2248.93633177, 1908.92844943,
479.18330748, 550.09264769, 581.27775562, 602.90277249, 729.74280191,
963.299432, 1186.40357135, 1377.06205603, 1604.97385043, 1977.32706598,
1528.89847687, 2017.83048618, 2558.91142867, 2422.08428098, 2418.86951627,
2248.93633177, 1908.92844943), t_exp_reg = c(26.16551766, 32.54411008,
31.89983946, 33.57790402, 40.57386933, 51.27728681, 72.02726694,
85.89296127, 96.54878305, 125.99423998, 100.51912523, 158.86908483,
208.20248928, 176.42267237, 190.65640004, 176.10542289, 130.7703496,
32.71137458, 39.35283051, 40.59087882, 45.3692821, 60.72202556,
80.76792966, 105.34277987, 116.81838439, 132.64802812, 168.07775832,
112.32696236, 144.44785762, 184.26048785, 181.47032946, 169.40245823,
153.22527354, 144.68736618, 7.74947477, 11.5467708, 15.111152,
16.76515862, 20.21513219, 32.21155115, 49.08098119, 49.34752514,
65.23062284, 90.83448565, 98.68533335, 110.35181638, 155.20134044,
184.11839864, 202.12998344, 202.38291918, 186.14894147, 300.17015871,
338.94189249, 347.69477529, 355.54335399, 419.69931314, 554.38578988,
691.16322191, 839.23036408, 957.08705321, 1162.56265848, 872.12931417,
1206.33027022, 1521.9238857, 1400.98004137, 1300.24106912, 1249.64540352,
1029.14047836, 112.38678176, 127.70704381, 145.98111005, 151.64707376,
188.53246169, 244.6568745, 268.78932144, 285.77282115, 353.45936321,
429.85792355, 345.23774176, 397.83145713, 489.3232254, 479.09283914,
556.43960544, 467.57731264, 418.18131382), year = c(1999L, 2000L,
2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L,
2010L, 2011L, 2012L, 2013L, 2014L, 2015L, 1999L, 2000L, 2001L,
2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L,
2011L, 2012L, 2013L, 2014L, 2015L, 1999L, 2000L, 2001L, 2002L,
2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L,
2012L, 2013L, 2014L, 2015L, 1999L, 2000L, 2001L, 2002L, 2003L,
2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L,
2013L, 2014L, 2015L, 1999L, 2000L, 2001L, 2002L, 2003L, 2004L,
2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L), NO_REGIAO_UF = structure(c(4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L
), .Label = c("REGIAO SUDESTE", "REGIAO SUL", "REGIAO CENTRO OESTE",
"REGIAO NORTE", "REGIAO NORDESTE", "REGIAO NAO DECLARADA"), class = "factor")), row.names = c(NA,
-85L), class = c("data.table", "data.frame"))
plot_tot<-structure(list(t_exp = c(479.18330748, 550.09264769, 581.27775562,
602.90277249, 729.74280191, 963.299432, 1186.40357135, 1377.06205603,
1604.97385043, 1977.32706598, 1528.89847687, 2017.83048618, 2558.91142867,
2422.08428098, 2418.86951627, 2248.93633177, 1908.92844943),
year = 1999:2015, scaled = c(284.99639069633, 327.170034291692,
345.717515109138, 358.579089501427, 434.017757786058, 572.926596136247,
705.618769406107, 819.013746111758, 954.565293478285, 1176.0240146804,
909.319128707865, 1200.1136029187, 1521.9238857, 1440.54533466909,
1438.63333914465, 1337.56482635206, 1135.34363508228)), row.names = c(NA,
-17L), class = c("data.table", "data.frame"))
plot\u tot致以最诚挚的问候您可以通过为
线型添加一个单独的键来完成此操作：
ggplot（plot_1，aes（x=year，y=t\u exp\u reg，color=NO\u REGIAO\u UF））+
geom_线（）+
实验室（title=“按地区出口”，x=“年份”，
y=“按地区划分的出口总额（1亿美元）”，fill=“地区”）+
几何线（数据=曲线图），
aes（y=标度，
x=年，
线型=系数（“总计”），
inherit.aes=FALSE，size=0.8）+
比例\线型\手动（值=c（2），中断=“总计”）+
连续刻度（断开=顺序（0，2600，400），
秒轴=秒轴（~.*scl，
name=“巴西出口总额（1亿美元）”+
比例x连续（中断=顺序（1990、2015、3））+
实验室（颜色=“区域”，线型=”）+
主题（legend.key.width=单位（30，“点”））
您可以通过为线型添加单独的键来执行此操作：
ggplot（plot_1，aes（x=year，y=t\u exp\u reg，color=NO\u REGIAO\u UF））+
geom_线（）+
实验室（title=“按地区出口”，x=“年份”，
y=“按地区划分的出口总额（1亿美元）”，fill=“地区”）+
几何线（数据=曲线图），
aes（y=标度，
x=年，
线型=系数（“总计”），
inherit.aes=FALSE，size=0.8）+
比例\线型\手动（值=c（2），中断=“总计”）+
连续刻度（断开=顺序（0，2600，400），
秒轴=秒轴（~.*scl，
name=“巴西出口总额（1亿美元）”+
比例x连续（中断=顺序（1990、2015、3））+
实验室（颜色=“区域”，线型=”）+
主题（legend.key.width=单位（30，“点”））
太好了，这非常有用！您是否也知道如何使第二个y轴上的标签与主y轴上的标签在同一方向上可读？问题是，一个是自上而下的，另一个是自下而上的伟大，这是超级有用！您是否也知道如何使第二个y轴上的标签与主y轴上的标签在同一方向上可读？问题是一个是自上而下的，另一个是自下而上的
scl <- max(plot_tot$t_exp)/max(plot_1$t_exp_reg)
ggplot(plot_1, aes(x = year, y = t_exp_reg, color = NO_REGIAO_UF)) +
geom_line() +
labs(title = "Export by Region", x = "Year", y = "Total Export by region (100M US$)", fill = "Region") +
geom_line(data =plot_tot,aes(y = scaled, x = year),inherit.aes = FALSE, color="#362828",size = 0.8,linetype=2)+
scale_y_continuous(breaks=seq(0, 2600, 400), sec.axis = sec_axis(~.*scl, name = "Brazil total exports (100M US$)")) +
scale_x_continuous(breaks = seq(1990,2015,3)) +
labs(color = "Legend")