显示第二个 geom_point() 的相应图例

Question

我在同一个情节中用 geom_point 绘制了三次，但第二次和第三次 geom_point 没有出现在图例中，我不明白为什么。我看了很多帖子，但找不到真正有效的解决方案。我的 2 个原始数据框不同，我更愿意保持这种状态而不加入它们。

十字（或颜色）出现在所有图例项上，或者第二个 geom_point() 未在图例中提及。这是我当前的代码：

ggplot () +
  geom_point(data = data_1[data_1$River != "Roya",], aes(x = W_AC, y = BRI_mean_XS, shape = River, col = Type), size = 3) +
  geom_point(data = data_2, aes(x = W_m, y = BRI_norm, color = "Second geom_point "), shape = 4, size = 2.5) + 
  scale_shape_manual(values = c(15, 18, 17, 16)) +
  scale_colour_manual(values = c("blue4", "chocolate1", "darkcyan")) +
  geom_text(data = data_1[data_1$River != "Roya",], aes(x = W_AC, y = BRI_mean_XS, label = Year, vjust = -0.5, hjust = -0.5), show.legend = FALSE, size = 4) +
  scale_x_continuous(name = "aa") +
  scale_y_continuous(name = "bb") + 
  geom_point(data = data_1[data_1$River == "Roya",], aes(x = W_AC, y = BRI_mean_XS), shape = 16, col = "cornflowerblue", size = 3) +
  geom_text(data = data_1[data_1$River == "Roya",], aes(x = W_AC, y = BRI_mean_XS, label = Year, vjust = -0.5, hjust = -0.5), show.legend = F, size = 4) +
  theme_bw()

我还尝试在 scale_*_manual 中指定颜色和形状，但绘图中未使用该形状。例如：scale_shape_manual(values = c(15, 18, 17, 16, 4))，4代表第二个geom_point。

正如我在其他帖子中读到的，当在 scale_*_manual 中指定值时，它应该出现在图例中的后面，但在这里它似乎混淆了。 Type 部分或 River 部分不能显示蓝色叉号吗？第三个也是一样geom_point()（Roya）可以在River部分画一个蓝色圆圈吗？

这是我的 2 个数据帧的输入：

data_1:

structure(list(River = c("Durance", "Durance", "Durance", "Durance",  "Roya", "Var", "Drac", "Drac", "Drac", "Drac", "Var", "Var",  "Mareta", "Mareta", "Mareta", "Mareta", "Var"), Type = c("Under restoration",  "Target", "Under restoration", "Target", "Witness", "Under restoration",  "Under restoration", "Target", "Under restoration", "Target",  "Target", "Under restoration", "Under restoration", "Under restoration",  "Target", "Target", "Under restoration"), Year = c(2017, 2017,  2012, 2012, 2018, 2005, 2011, 2011, 2018, 2018, 2012, 2018, 2005,  2013, 2005, 2013, 2012), BRI_mean_XS = c(0.0028, 0.0017, 0.0033, 
0.0018, 0.009, 0.0097, 0.0182, 0.0026, 0.0032, 0.0035, 0.0053, 
0.0016, 0.005, 0.0041, 0.0058, 0.0082, 0.0037), W_AC = c(296.522411128284, 
411.01376146789, 263.944186046512, 363.288990825688, 88.6420798065296, 
155.868223887175, 41.4430051813472, 138.772532188841, 105.525906735751, 
108.848484848485, 144.78431372549, 314.685764654033, 29.8791208791209, 
52.8, 33.6949152542373, 34.4661016949153, 149.838539375275)), row.names = c(NA, 
-17L), class = c("tbl_df", "tbl", "data.frame"))

data_2:

structure(list(SITE = c("AIGUES-C", "BUECH-AV", "ARRONDINE",  "ARVAN", "ASSE-BLIEUX", "ASSE-BLIEUX", "ASSE-AV", "ASSE-AM",  "ASSE-AM", "BES-BLEONE", "BES-BLEONE", "BES-DROME", "BES-DROME",  "BLEONE-AM", "BLEONE-AV", "BUECH-AV", "BUECH-AV", "DRANSE-MORZINE",  "DRANSE-MORZINE", "DROME-RECOUBEAU", "DROME-PONTQUART", "DROME-PONTQUART",  "EYGUES-R", "FIER", "GIFFRE", "JABRON", "PETIT-BUECH", "PETIT-BUECH",  "ROUBION", "SASSE", "SASSE", "SASSE", "SEVERAISSE", "SEVERAISSE",  "UBAYE", "VANCON", "VAR", "VENEON", "VERDON", "DRAC LIDAR1",  "DROME LIDAR1", "DROME LIDAR2", "DROME LIDAR3"), W_m = c(180, 
333.593594745271, 56, 78, 102, 58.8, 171.9, 202, 170, 132, 148,  76, 98, 99.9, 171.3, 214, 125, 63, 64, 137, 181, 39, 66, 91,  220, 120, 90, 103, 114, 182, 123, 139, 152, 38, 144, 58, 183,  193, 193,
103.3287640678, 170.959110791, 168.800988262, 133.13237116 ), BRI_norm = c(0.00238417932933424, 0.0019586918252209, 0.00592873427970417, 
0.00496998572378169, 0.00257768461027533, 0.00594823420965329, 
0.00196839869925125, 0.00110647254938539, 0.00129282468469599, 
0.00255415705319677, 0.00189636185539575, 0.00272918083912772, 
0.00362898036424863, 0.00240398604859984, 0.00158558538418367, 
0.00179786294819712, 0.0024557284827885, 0.00910376733031885, 
0.00534776094775883, 0.00392598083437978, 0.00240750522409946, 
0.00514878385829154, 0.00254279813562245, 0.00563806058644668, 
0.00119537585167636, 0.00458318564753459, 0.00595336684669024, 
0.00487895959784154, 0.00292014352039067, 0.00238157929363119, 
0.0025305005154242, 0.00243334672392244, 0.00211201916980846, 
0.007410716639085, 0.0035528851408779, 0.00991898865707844, 0.00350148630982832, 
0.00181290043814611, 0.00277563808425691, 0.00766507891511477, 
0.000968375521552066, 0.000999909065815609, 0.00107669687622853 )), row.names = c(NA, -43L), class = c("tbl_df", "tbl", "data.frame" ))

Answer 1

我希望这是向前迈出的有益一步，但不完全确定它是否完成了您正在寻找的情节。本质上，您应该采取两个进一步的步骤来获得图例中的所有内容并按顺序排列：

任何你想出现在图例中的东西都应该在每个 aes() 调用中，每个 geom_point()
在 scale_*_manual() 调用中使用 breaks = 参数可让您指定应显示的所有内容及其应显示的顺序。

与这两者一起工作，这可能就是您正在寻找的东西的开始：

library(ggplot2)

# the parts of the plot I haven't changed (separated for clarity)

p_base <- ggplot () +
  geom_text(
    data = data_1[data_1$River != "Roya", ],
    aes(
      x = W_AC,
      y = BRI_mean_XS,
      label = Year,
      vjust = -0.5,
      hjust = -0.5
    ),
    show.legend = FALSE,
    size = 4
  ) +
  scale_x_continuous(name = "aa") +
  scale_y_continuous(name = "bb") +
  geom_text(
    data = data_1[data_1$River == "Roya", ],
    aes(
      x = W_AC,
      y = BRI_mean_XS,
      label = Year,
      vjust = -0.5,
      hjust = -0.5
    ),
    show.legend = F,
    size = 4
  ) +
  theme_bw()

# Parts I've changed

p_base + geom_point(
  data = data_1[data_1$River != "Roya",],
  aes(
    x = W_AC,
    y = BRI_mean_XS,
    shape = River,
    col = Type
  ),
  size = 3
) +
  geom_point(
    data = data_2,
    aes(
      x = W_m,
      y = BRI_norm,
      shape = "Second geom_point",
      color = "Second geom_point"
    ),
    size = 2.5
  ) +
  scale_shape_manual(
    breaks = c("Drac", "Durance", "Mareta", "Roya", "Var", "Second geom_point"),
    values = c(15, 18, 17, 16, 10, 4)
  ) +
  scale_colour_manual(
    breaks = c("Target", "Under restoration", "Second geom_point", "Roya"),
    values = c("blue4", "chocolate1", "darkcyan", "cornflowerblue")
  ) +
  geom_point(
    data = data_1[data_1$River == "Roya",],
    aes(
      x = W_AC,
      y = BRI_mean_XS,
      shape = "Roya",
      col = "Roya"
    ),
    size = 3
  )

^{由 reprex package (v2.0.0)}

于 2021-04-07 创建

Answer 2

我真的不是以下方法的忠实粉丝（使用适当的映射来解决这个问题会更惯用）但是你可以通过覆盖 color / shape 来快速解决这个问题River 和 Type 传说中的美学符合您的喜好：

通过将 shape 美学移入 aes 并从 River 映射来修改您的第三个点图层：

aes(x = W_AC, y = BRI_mean_XS, shape = River)

调整形状比例，使 Roya 由圆圈 (16) 表示：

scale_shape_manual(values = c(15, 18, 17, 16, 16))

使用guides()覆盖图例中的美学：

 + guides(
    color = guide_legend(
        override.aes = list(shape = c(4, 16, 16))
    ),
    shape = guide_legend(
        override.aes = list(color = c(rep("black", 3), "cornflowerblue", "black"))
    )
  )

结果：

显示第二个 geom_point() 的相应图例

Show corresponding legend for second geom_point()

r

ggplot2

geom-point