如何使用图例在末尾创建带有单个几何点的几何线图
我想重现我在《纽约时报》上找到的情节：
dput数据是：
structure(list(`Gss year for this respondent` = c(1977, 1977,
1977, 1978, 1978, 1978, 1980, 1980, 1980, 1982, 1982, 1982, 1983,
1983, 1983, 1984, 1984, 1984, 1985, 1985, 1985, 1987, 1987, 1987,
1988, 1988, 1988, 1989, 1989, 1989, 1990, 1990, 1990, 1991, 1991,
1991, 1993, 1993, 1993, 1994, 1994, 1994, 1996, 1996, 1996, 1998,
1998, 1998, 2000, 2000, 2000, 2002, 2002, 2002, 2004, 2004, 2004,
2006, 2006, 2006, 2008, 2008, 2008, 2010, 2010, 2010, 2012, 2012,
2012, 2014, 2014, 2014, 2016, 2016, 2016, 2018, 2018, 2018),
`Political party affiliation` = c("Democrat", "Independent",
"Republican", "Democrat", "Independent", "Republican", "Democrat",
"Independent", "Republican", "Democrat", "Independent", "Republican",
"Democrat", "Independent", "Republican", "Democrat", "Independent",
"Republican", "Democrat", "Independent", "Republican", "Democrat",
"Independent", "Republican", "Democrat", "Independent", "Republican",
"Democrat", "Independent", "Republican", "Democrat", "Independent",
"Republican", "Democrat", "Independent", "Republican", "Democrat",
"Independent", "Republican", "Democrat", "Independent", "Republican",
"Democrat", "Independent", "Republican", "Democrat", "Independent",
"Republican", "Democrat", "Independent", "Republican", "Democrat",
"Independent", "Republican", "Democrat", "Independent", "Republican",
"Democrat", "Independent", "Republican", "Democrat", "Independent",
"Republican", "Democrat", "Independent", "Republican", "Democrat",
"Independent", "Republican", "Democrat", "Independent", "Republican",
"Democrat", "Independent", "Republican", "Democrat", "Independent",
"Republican"), value = c("Yes",
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes",
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes",
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes",
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes",
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes",
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes",
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes",
"Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes", "Yes",
"Yes", "Yes", "Yes", "Yes", "Yes"), n = c(226L, 191L, 130L,
188L, 194L, 109L, 210L, 235L, 127L, 281L, 264L, 127L, 174L,
200L, 139L, 176L, 220L, 140L, 200L, 192L, 147L, 285L, 227L,
161L, 142L, 113L, 80L, 159L, 122L, 113L, 124L, 136L, 115L,
142L, 127L, 129L, 180L, 161L, 112L, 351L, 311L, 207L, 306L,
299L, 202L, 283L, 280L, 141L, 246L, 306L, 128L, 144L, 160L,
77L, 138L, 121L, 80L, 307L, 290L, 156L, 214L, 198L, 117L,
199L, 227L, 91L, 245L, 209L, 80L, 306L, 310L, 97L, 342L,
337L, 127L, 300L, 333L, 96L), Percent = c(0.336, 0.38, 0.392,
0.311, 0.352, 0.306, 0.375, 0.419, 0.383, 0.327, 0.426, 0.363,
0.283, 0.37, 0.356, 0.324, 0.421, 0.381, 0.337, 0.416, 0.325,
0.352, 0.41, 0.385, 0.398, 0.334, 0.292, 0.407, 0.425, 0.333,
0.416, 0.455, 0.377, 0.409, 0.398, 0.419, 0.483, 0.445, 0.354,
0.485, 0.471, 0.375, 0.479, 0.421, 0.378, 0.427, 0.409, 0.295,
0.403, 0.407, 0.286, 0.462, 0.475, 0.307, 0.466, 0.382, 0.307,
0.488, 0.374, 0.293, 0.463, 0.396, 0.343, 0.49, 0.433, 0.312,
0.538, 0.421, 0.274, 0.536, 0.44, 0.271, 0.531, 0.461, 0.298,
0.607, 0.513, 0.283)), class = c("grouped_df", "tbl_df",
"tbl", "data.frame"), row.names = c(NA, -78L), groups = structure(list(
`Gss year for this respondent` = c(1977, 1977, 1977, 1978,
1978, 1978, 1980, 1980, 1980, 1982, 1982, 1982, 1983, 1983,
1983, 1984, 1984, 1984, 1985, 1985, 1985, 1987, 1987, 1987,
1988, 1988, 1988, 1989, 1989, 1989, 1990, 1990, 1990, 1991,
1991, 1991, 1993, 1993, 1993, 1994, 1994, 1994, 1996, 1996,
1996, 1998, 1998, 1998, 2000, 2000, 2000, 2002, 2002, 2002,
2004, 2004, 2004, 2006, 2006, 2006, 2008, 2008, 2008, 2010,
2010, 2010, 2012, 2012, 2012, 2014, 2014, 2014, 2016, 2016,
2016, 2018, 2018, 2018), `Political party affiliation` = c("Democrat",
"Independent", "Republican", "Democrat", "Independent", "Republican",
"Democrat", "Independent", "Republican", "Democrat", "Independent",
"Republican", "Democrat", "Independent", "Republican", "Democrat",
"Independent", "Republican", "Democrat", "Independent", "Republican",
"Democrat", "Independent", "Republican", "Democrat", "Independent",
"Republican", "Democrat", "Independent", "Republican", "Democrat",
"Independent", "Republican", "Democrat", "Independent", "Republican",
"Democrat", "Independent", "Republican", "Democrat", "Independent",
"Republican", "Democrat", "Independent", "Republican", "Democrat",
"Independent", "Republican", "Democrat", "Independent", "Republican",
"Democrat", "Independent", "Republican", "Democrat", "Independent",
"Republican", "Democrat", "Independent", "Republican", "Democrat",
"Independent", "Republican", "Democrat", "Independent", "Republican",
"Democrat", "Independent", "Republican", "Democrat", "Independent",
"Republican", "Democrat", "Independent", "Republican", "Democrat",
"Independent", "Republican"), .rows = list(1L, 2L, 3L, 4L,
5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 15L, 16L,
17L, 18L, 19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L,
28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L, 37L, 38L,
39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L,
dc3*_*c37 10
对于geom_pointand geom_text，您可以通过仅保留去年（2018 年）来对数据框进行子集化：
ggplot(df, aes(x = `Gss year for this respondent`, y = Percent*100))+
geom_line(aes(color = `Political party affiliation`), show.legend = FALSE)+
geom_point(data = df[df$`Gss year for this respondent` == max(df$`Gss year for this respondent`),],
aes(x =`Gss year for this respondent`, y = Percent*100, color = `Political party affiliation`), show.legend = FALSE)+
geom_text(data = df[df$`Gss year for this respondent` == max(df$`Gss year for this respondent`),],
aes(x =`Gss year for this respondent`,
y = Percent*100,
colour = `Political party affiliation`,
label = `Political party affiliation`), show.legend = FALSE, hjust = -0.1)+
xlim(1975, 2026)+
ylim(0,80)+
scale_color_manual(values = c("blue","green","red"))
以下是对 @dc37 答案的一些更新，使 OP 更接近所需的情节。需要明确的是，@dc37 的答案解决了主要问题：如何绘制系列中的最后一个点。所有这些都太多了，无法作为 @dc37 答案的评论添加，因此我将其作为单独的解决方案发布 - 尽管它实际上更多的是 @dc37 答案的扩展，而不是一个独特的替代方案。
更新
修复了 x 轴范围，以便在轴停止后出现注释
删除注释中的颜色
消除绘图上 x 轴线和 y=0 之间的空间
在 x 轴刻度线周围创建空间（轴线和刻度文本之间的空间）
显示主要 y 轴网格线
使 x 和 y 刻度与原始刻度相匹配
Run Code Online (Sandbox Code Playgroud)ggplot(df, aes(x = `Gss year for this respondent`, y = Percent*100, color = `Political party affiliation`)) + geom_line(show.legend = FALSE, size = 1) + geom_point(data = point_df, aes(x =`Gss year for this respondent`), show.legend = FALSE, size = 2) + scale_x_continuous(breaks = seq(1980, 2015, by = 5)) + scale_y_continuous(limits = c(0, 80), breaks = seq(0, 80, by = 20), expand = c(0, 0)) + scale_color_manual(values = c("deepskyblue1","gray80","firebrick3")) + geom_text(data = point_df, aes(x = 2019, y = Percent*100, label = `Political party affiliation`), color = "black", show.legend = FALSE, hjust = -0.1) + coord_cartesian(xlim = c(1978, 2016), clip = 'off') + theme(plot.margin = unit(c(1,7,1,1), "lines"), panel.grid.major.y = element_line(color = "gray90"), axis.line.y = element_blank(), axis.ticks.length.x = unit(.3, units = "cm"), axis.ticks.x = element_line(linetype = 2)) + labs(y = "", x = "")
重要
从 OP 的数据生成的图表 - 在 OP 的代码中复制，以及这个答案和 @dc37 的答案 - 看起来与原始屏幕截图略有不同。（看看线条如何不以同样的方式相互重叠。）我还没有深入研究这一点 - 这里的更新主要集中在化妆品上。
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